Second Time Lucky? Withdrawn IPOs that Return to the Market

Craig G. Dunbar and Stephen R. Foerster*

Richard Ivey School of Business The University of Western Ontario

London, Ontario, Canada, N6A 3K7

Abstract

Our study presents an investigation of issuers that withdraw from the IPO market (after security regulation filings) that successfully return later. We examine over 7000 IPO filings from 1985 to 2000 and find that 20% of the filings are withdrawn. We identify 138 firms, or 9% of the withdrawn sample, that successfully return to the market. Probit analysis identifies venture capital backing and reputation of the lead underwriter as key factors in predicting successful return. The possibility of returning has a significant impact on the choice to withdraw and the pricing of offerings that succeed. Firms less likely to get a second chance are more likely to proceed with their IPO. Those firms going ahead with an IPO that were more likely to fail and less likely to return also are more likely to cut offering prices to assure success. Our sample or returning IPOs also provides a unique context in which to investigate underwriter switching after a withdrawal but before a successful IPO, complementing the existing literature on switching after a successful IPO but before a subsequent equity offering. We find that switching occurs in response to poor bank performance and when switching firm’s “graduate” to banks that have high industry market shares. Current version November 14, 2003, 2003, 2003 JEL Classification Codes: G14, G24, G32. Key Words: IPOs, withdrawals, return performance, investment bank reputation, switching. *Associate Professor and Paul Desmarais/ London Life Finance Fellow, respectively. We wish to thank Mark Huson, Kathy Kahle, Kai Li, Michelle Lowry, Gordon Roberts, Tim Simin, Chad Zutter, Lee Ann Woo, seminar participants at the University of Arkansas, University of British Columbia, York University, Queens University, the University of Pittsburgh, the Northern Finance Association Meetings (2002), the Financial Management Association Meetings (2003) and especially Colette Southam for excellent research assistance. We also thank the Social Sciences and Humanities Research Council for financial support. Address correspondence to: Craig Dunbar, phone: 1-519-661-3716; fax: 1-519-661-3959; e-mail: cdunbar@ivey.uwo.ca; or Steve Foerster, phone: 1-519-661-3726; fax 1-519-661-3485; e-mail: sfoerster@ivey.uwo.ca.

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1. Introduction

Arguably the most significant event in the life of a corporation is its transition from a private

company to a public company through the initial public offering (IPO) process. The IPO provides a

major source of capital to the corporation and allows the existing owners to have a liquid market for their

shares. Firms rely on the IPO for either their survival or their ability to take advantage of growth

opportunities.

Yet not all firms are successful in making the transition from a private to public company. In

fact, after an IPO process has been initiated with the support of an investment bank, a surprisingly large

number of proposed IPOs are withdrawn from the market before being completed. An emerging literature

examines the prevalence of proposed IPOs that are registered but withdrawn before issue.1 For example,

Dunbar (1998) and Busaba, Benveniste and Guo (2001) show that between the mid-1980s and mid-1990s

almost one in five IPOs was withdrawn. Evidence from more recent periods, as uncovered in this paper,

suggests that this fraction has increased to over one in two in some years. Several studies have attempted

to explain the choice to withdrawal an IPO. Busaba, Benveniste and Guo (2001) argue that the choice of

an issuer to withdraw an IPO should depend on the issuer’s reservation value for the offering relative to

possible investor valuations. Welch (1992) argues that negative information “cascades” can result in

investor valuations falling below a level deemed reasonable by issuers, resulting in withdrawal. Dunbar

(1998) , however, finds that issuers withdrawing IPOs are unlikely to return for a successful public equity

offering. If withdrawals are in response to temporary market misvaluations, it is surprising so few firms

return. The choice to withdraw, therefore, remains puzzling since it can significantly restrict a firm’s

access to the liquid and relatively inexpensive public capital markets.

To gain insights into the choice of withdrawal, we examine a sample of firms that withdraw their

IPO but are able to return eventually to the public equity markets for a successful IPO. We first attempt

1 In a related literature, Mikkelson and Partch (1988) and Clarke, Dunbar and Kahle (2001) examine withdrawn seasoned equity offerings.

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to identify the factors that affect a withdrawn issuer’s likelihood of being able to return successfully for

an IPO. We find that firm’s initially brought forward by more reputable investment banks, and those

having venture capital backing are more likely to return. In other words, issues that have more ex ante

certification have a better chance of surviving the negative event of a withdrawal. Market conditions at

the time of the withdrawal and afterwards also have an impact on an issuer’s ability to return. Issues

withdrawn in more active IPO markets, when interest rates are high and when market returns are low are

more likely to be able to return.

Since the likelihood of returning is predictable, we next examine whether this likelihood affects

the firm’s choice to withdraw. We find that the probability of withdrawal is positively related to the

like lihood of successful return. Issuers that face the choice to withdraw but do not expect to get a second

chance are more likely to try to push forward and complete their IPO. The likelihood of withdrawal and

possibility of return should also impact the pricing of successful IPOs. In order to ensure success, firms

expected to withdrawal with a low chance of returning should be more likely to cut prices during the

bookbuilding process. Controlling for commonly used variables in the literature, we find that price

adjustments are more negative for these firms.

Overall, the evidence indicates that firms consider the costs of withdrawal when attempting to

decide whether or not to proceed with an IPO. Firms not likely to get a second chance are more likely to

push forward, even though this might require that the issuer more substantially cut prices than would be

expected. Our study makes a number of additional contributions to the literature on IPO withdrawals.

First we extend the analysis in Dunbar (1998), Busaba, Benveniste and Guo (2001) and Benveniste,

Ljungqvist, Wilhelm and Yu (2002) on the determinants of offering withdrawal. Dunbar examines 3,540

withdrawn and successful IPOs from 1984 to 1993 and relates the choice to withdraw to a short list of

four observable variables. Busaba, Benveniste and Guo (2001) consider a larger number of variables

obtained directly from IPO prospectuses but only study 536 IPO filings from 1990 to 1992. Benveniste,

Ljungqvist, Wilhelm and Yu (2002) look at a longer time period (1985 to 2000) but focus on a number of

market measures proxying for “information spillovers”. Like Benveniste et. al., we look at a longer time

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period but also examine a wider range of market and firm specific variables.2 Some new variables

emerge as very important in explain ing IPO withdrawals. The most significant variable in our probit

model, economically and statistically, is the industry market share of the investment bank in the IPO.

Issuers brought forward by banks having a significant presence in the industry of the issuer are more

likely to be successful. Other significant new explanatory variables include corporate bond yield spreads,

the industry average book-to-market ratio, and the return on the Nasdaq composite index around filing.

An interesting feature of the sample of returning IPOs is that in approximately 75% of the cases,

the investment bank leading the successful IPO is different than the bank used in the initial unsuccessful

attempt. Withdrawn IPOs that subsequently return to the market, therefore, provides a unique setting to

explore underwriter switching. James (1992) examines firms that switch underwriters subsequent to an

IPO. Krigman, Shaw and Womack (2001) update James’ analysis and consider a wider range of

alternative explanations for underwriter switching including mispricing of the offering (leaving too much

money on the table), poor share placement resulting in high flipping, limited market making activity,

limited research coverage and graduation (simply moving to a bank with greater reputation). They find

that graduation and limited research coverage are the most significant determinants of switching and

conclude that “there is little evidence that firms switch due to dissatisfaction with underwriter

performance at the time of the IPO” (p. 245).

We believe that an examination of switching decisions after an IPO provides a possibly biased

view of the importance of different roles played by investment banks in the IPO process. Firms returning

for follow-on equity offerings not only had a successful IPO but also generally experienced very positive

stock market performance after the IPO (numerous studies show that stock prices significantly ramp up

prior to a follow-on equity offering). It would be very surprising, in this setting, for a firm to express

dissatisfaction with work done by its IPO underwriter. However, this does not diminish the importance of

the investment bank’s role in the successful pricing and placement of shares as part of the IPO process.

2 Firm specific data for withdrawn filings is generally not readily available from standard data sources. We expand our sample by gathering data with prospectus level information through the SEC’s Edgar system.

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An examination of underwriter switching following a withdrawn IPO is a very different context

and should provide complementary insights into the importance of various investment bank roles. In the

context of a withdrawn IPO, the decision to subsequently switch investment bank cannot be explained by

many of the alternatives proposed by Krigman Shaw and Womack (2001): leaving too much money on

the table, dissatisfaction with retail/institutional investor mix, market making by the IPO underwriter or

subsequent research coverage. All of these considerations require that the IPO be completed. However,

firms may switch because of dissatisfaction with the investment bank’s efforts in original failed IPO

process (the performance hypothesis) or because they can now obtain the services of a more reputable

underwriter (the graduation hypothesis). Conversely, firms may choose not to switch after an

unsuccessful IPO if they have confidence in the underwriter and view the previous failed IPO as related to

other external and uncontrollable factors such as an unfriendly market environment.

We find evidence supportive of both the graduation and performance stories. The percentage

increase in proceeds sought is much greater for firm’s switching banks, consistent with the performance

story (issuers are unhappy that the initial bank was unsuccessful when attempting a relatively small

offering). The new bank also typically has much higher industry market share than the bank leading the

first attempt. Knowing the importance of industry presence (as noted above), issuers move to banks more

likely to complete the offering on second attempt, consistent also with graduation.

The remainder of the paper is organized as follows. In section 2 we describe the data used in our

analysis. We develop hypotheses and present evidence on the factors affecting the choice to withdraw an

IPO in section 3. Evidence on factors affecting the successful return to the IPO market after withdrawal

is presented in section 4. We examine the underwriter switching choice for withdrawn IPOs that return to

the market in section 5. The effect of underwriter switching and the possibility of returning on the choice

to withdraw is examined in section 6. The effect of the possibility of withdrawal on the pricing of

successful IPOs is examined in section 7. Finally, we present conclusions in section 8.

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2. Data

Our study examines all U.S. firms that file documents to raise capital through a firm commitment

initial public offering of equity between 1985 and 2000. 3 Our primary data source is Thomson Financial

Securities Data’s (TFSD) New Issues Database. We begin our analysis in 1985 as TFSD’s coverage of

withdrawn IPOs begins in 1984 but is complete only beginning in January 1985. We consider all IPOs

filed over that period but, following the existing literature (e.g., Busaba, Benveniste and Guo, 2001), we

screen offerings on a number of criteria. Specifically, we exclude unit offerings (combinations of equity

and warrants), REITs, ADRs and closed-end mutual funds.4 For each offering, we gather data from

TFSD on firm characteristics (e.g., data from past financial statements) and offering characteristics

including offering size, price, and investment bank reputation. Data on market returns around the

proposed offerings are collected from the CRSP database. Data on market interest rates around the

proposed offerings are obtained from the Federal Reserve Bank of St. Louis web site

(http://research.stlouisfed.org/fred2/). For many withdrawn offerings, TFSD data are incomplete. To

increase our coverage of withdrawn offerings we obtain initial prospectuses from the SEC’s Edgar system

for all withdrawn IPOs staring in 1996 (electronic filing only began in the mid 1990s). Offering

characteristics (proposed price and size) and past financial information are then obtained for these

offerings.

TFSD data allow us to identify all successful IPOs as well as all withdrawn IPOs. It is somewhat

more challenging to identify which successful IPOs were previously withdrawn and return to the market.

We use a number of approaches to identify those returners. The first step in identifying matches is to

examine unique company identifier numbers (CUSIPs) assigned to issuers by TFSD. CUSIPs from

TFSD’s withdrawn IPO dataset are matched to TFSD’s database of successful IPOs. In many cases,

3 Ritter (1987), Cho (1992) and Dunbar (1998) also examine withdrawals within the context of best-efforts offering methods. 4 Unlike Busaba, Benveniste and Guo (2001), we do not screen out firms in certain industries such as financials or service firms.

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CUSIPs assigned to companies are different on TFSD’s databases.5 We use a number of other

approaches to identify returning IPOs. TFSD provide a contact name for each issuer in its database. We

look for common names in the two databases. TFSD also provides information on business location,

which we use as a check. In other cases we look for name matches (using parts of names). As a last step,

where possible, we check our matches of withdrawn and successful offerings using actual filing

documents from Edgar to ensure that the matches are correct. In spite of our best efforts, we recognize

that it is likely that we have missed some returning issuers.

In Table 1 we report the number of observations in our initial database, broken down by filing

year and ultimate outcome (completed or withdrawn offering and for withdrawn offerings we report the

number of cases where the firm returns for a successful IPO). Overall we have 7,442 firms in our

database, 1,473 of which were withdrawn (approximately 20%). Of those firms withdrawing an IPO only

138 (or a little over 9%) ever return for a successful offering. The number of filings varies considerably

over time from a low of 154 in 1989 to a high of 824 in 1995. The percentage of withdrawn IPOs range

from 8.88% in 1991 to a staggering 55.29% in 2000. The percentage of successful returns also varies

considerably over time from 0.34% in 2000 to 17.31% in 1992. Ignoring the more recent two years (since

many of those firms have not had time to return), the lowest rate of successful returns is 2.70% in 1985. 6

3. Determinants of the Choice to Withdraw an IPO

In this section we examine factors affecting the choice to withdraw an IPO. Dunbar (1998) relies

on three theories of the IPO market to make predictions regarding the determinants of IPO withdrawal.

Benveniste and Spindt (1989) present a model where investment banks precommit to allocation and

5 As an example, Goldman Sachs is assigned a different CUSIP number in the withdrawn IPO file and the successful IPO file. This is likely due to the fact that the firm was structured as a limited partnership in its original filing and an incorporated business in its eventual successful offering. 6 The correlation between annual number of filings and annual number of withdrawals is 0.50. The correlation between annual percentage of withdrawals and percentage of those withdrawals that return is –0.25 (although it is 0.37 if the last two years are excluded).

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pricing schemes that induce investors to truthfully reveal information regarding the value of securities

being issued prior to final pricing. When information revealed is sufficiently negative, offerings can be

withdrawn. Benveniste and Spindt argue that negative information is more likely to arise in offerings by

firms whose value, ex ante, is more uncertain. This suggests that offerings by firms with greater ex ante

valuation uncertainty are more likely to be unsuccessful. Welch (1992) presents a model where investors

have some ability to “eye” the demand of prior investors contacted to purchase shares. Offerings can be

unsuccessful if early demand is weak. They are more likely to succeed if communication between

investors is reduced, however. Welch argues that investment banks play an important role in reducing

communication by offering shares diffusely (e.g., nationally or internationally). Offerings by banks that

place shares widely are more likely to succeed. Finally, Booth and Chua (1996) present a model of the

IPO market where information-gathering costs are reduced when offerings are clustered. This process

results in a greater precision of IPO valuation by investment banks, increasing the probability of offering

success (see Booth and Chua, pp. 298-299). Based on these theories, Dunbar (1998) relates withdrawal

choice to proxies for issuer riskiness (filing size and price), Carter and Manaster’s (1990) investment bank

reputation (as a proxy for breadth of share placement) and number of contemporaneous filings.

Busaba, Benveniste and Guo (2001) argue that the choice of an issuer to withdraw an IPO should

depend on the issuer’s reservation value for the offering relative to possible investor valuations.

Presumably, such a relative position is determined by factors affecting the issuer’s reservation value as

well as factors affecting investors’ valuations of the issue. Factors affecting issuer’s reservation value

should include the potential effect of withdrawal on firm survival and the firm’s access to alternative

sources of capital. Factors affecting investor valuation include proxies for firm riskiness (issuers that are

“tougher to value” should be discounted by investors), and issue certification (such as insider ownership

retention, investment bank reputation and venture capital backing).7

7 Potential investors in an initial public offering face an asymmetry of information commonly referred to as a lemons problem (Akerlof, 1970): since insiders have better information regarding the true value of their firm, they have an incentive to offer securities when they are overvalued by investors. Booth and Smith (1986) argue that this problem can be ameliorated if insiders credibly certify that they are not selling overpriced securities. One certification

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We consider a number of empirical measures to explain IPO withdrawal choice based on this

existing literature. First, we consider a number of issuer and issue characteristics that should be related to

deal riskiness. Average filing price is defined as the average of the low and high price indicated in the

initial prospectus. Filing size is the average filing price multiplied by the number of shares (in millions)

to be offered as indicated in the initial prospectus. In order to control for differences in filing dates, filing

sizes are measured in January 2000 dollars using CPI as a deflator. Firms with lower filing sizes and

prices tend to be riskier (see Seguin and Smoller 1997).

As a measure of the potential impact of an IPO withdrawal on firm survival, we use an industry

dummy variable as in Busaba, Benveniste and Guo (2001). Specifically , high-tech industry dummy is set

equal one when the issuer is from Fama and French (1997) industries 34 (business services) and 36

(chips). Withdrawal can cause bad publicity, negatively affecting the relationship between the firm and

various stakeholders including suppliers and customers. This problem is likely to be most acute for high-

tech firms where information asymmetries are likely to be most significant. Employees and suppliers are

also likely to have job-specific skills making withdrawal very costly (see Titman and Wessels, 1988).

Thus, we would expect the likelihood of withdrawal to be negatively related to our industry dummy.

Following Busaba, Benveniste and Guo (2001) we also consider a proxy for a firm’s access to

capital: a dummy variable taking the value 1 if the issuing firm has venture capital backing prior to the

filing date (Venture Capital backing dummy). Another measure of access to capital is a dummy variable

taking the value 1 if the primary use of proceeds in the IPO is to retire debt (Use of proceeds dummy).

Firms planning to retire debt and those with venture capital backing presumably have greater access to

capital and, therefore, would be less dependent on an IPO. This would suggest that the likelihood of

withdrawal should be positively related to the use of proceeds dummy and the venture capital dummy.8

mechanism is to hire an investment bank to manage the offering. This mechanism is credible if banks lose expected economic rents from future issues by being associated with an overpriced offering. Other mechanisms, such as insider retention and venture capital backing, also provide credible certification that the offering is not overpriced allowing the issuer to sell shares at more favorable terms (see Grinblatt and Hwang, 1989, and Lerner, 1994). 8 We considered other variables in our analysis used in prior studies including firm revenues pre filing, the firm’s pro forma market capitalization (number of shares to be outstanding multiplied by the expected offering price) and

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Alternatively, issues with venture capital backing could be argued to have greater certification. In this

case, the probability of withdrawal should be lower. Given this ambiguity, we leave it to the data to

determine which effect dominates.

We consider three measures of the investment bank’s characteristics in our analysis. Carter-

Manaster Rank is obtained from Carter and Manaster (1990) as updated by Carter, Dark and Singh (1998)

and more recently by Loughran and Ritter (2002b). These rankings are on a 0 to 9 scale, with 9 being the

most reputable underwriter. Second, Investment bank market share is measured for the bank taking the

firm public (see Dunbar, 2000). For each IPO we examine all IPOs in the year leading up to the offer

(including the IPO). We compute the sum of gross proceeds (on global shares excluding over allotments)

for which the underwriter was also the book manager. To account for mergers in the investment banking

industry, we gather data from TFSD on all combinations during the period. If the book manager recently

merged, the gross proceeds of all offering by any precedent bank are added together.9 In cases with

multiple book managers, equal credit is given to each bank. Market Share is then defined as the sum of

gross proceeds for the bank, divided by the sum of gross proceeds for all IPOs over the sample period.

Our third investment bank measure is the investment bank industry market share. Industry market share

is the sum of gross proceeds over the year prior to the IPO of all offerings in the same Fama-French

industry as the issuer where the book manager is same as the one in the current deal divided by the sum of

gross proceeds on all industry IPOs over the same period.

Offerings brought forward by banks with higher Carter-Manaster ranks, overall market shares and

industry market shares have greater certification. We would, therefore, expect that the likelihood of

withdrawal is lower for those issuers. Bates and Dunbar (2002) note that market share may also be

capturing a bank’s market power. If banks use this power to ensure deals get completed, the relationship

between market share and withdrawal should still be predicted to be negative.

In addition to issuer, issue and investment bank characteristics, we consider a number of variables

the firm’s debt to asset ratio. Neither variable was significant in our analysis, however. 9 For example, offerings by Salomon Smith Barney, all IPOs by Salomon Bros. and Smith Barney in the prior year

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reflecting market conditions at the time of the filing. As a measure of the intensity of the IPO market, we

include the number of IPO filings over the two months prior to the IPO’s filing date (number of filings

prior 2 months) in our analysis following Dunbar (1998) and Busaba, Benveniste and Guo (2001). As

discussed in previous research, market intensity can have two effects on withdrawals. In markets with

more filings, information spillovers become more significant, resulting in enhanced precision of valuation

(see Booth and Chua, 1996, and Benveniste, Ljungqvist, Wilhelm and Yu, 2002). This would suggest

that withdrawals are less likely in intense markets. Alternatively, the pool of available capital could be

limited suggesting that withdrawals are more likely in intense markets. Previous research indicates that

the latter effect dominates but we examine whether this remains true in our sample.

A second measure of market intensity considered is the number of filings over the two months

prior to an IPO in the same Fama-French industry as the issuer (number of industry filings prior 2

months). If information spillovers are more effective in reducing valuation uncertainty at the industry

level then this variable may do a better job of picking up this effect. Access to capital may remain

important at the industry level, however, so we again leave it to the data to determine what relationship

dominates.

We include two interest rate variables to provide information about market conditions at the time

of the filing. BAA-AAA yield spread at filing is defined as the difference between average rates on BAA

rated corporate bonds (by Moody’s) and AAA rated bonds. This yield spread is often used as an indicator

of default probabilities in the economy. In periods when the spread is large, probabilities of default are

expected to be higher. If negative firm information is more likely to arise in this market environment, we

would expect withdrawals to be more likely when spreads are higher. As an alternative view, access to

capital is often limited when spreads are large. Firms attempting to raise capital in high spread

environments may have few alternatives and are, therefore, less likely to cancel an IPO. The relationship

between yield spreads and the probability of withdrawal is ultimately, therefore, an empirical question.

The second interest rate variable is the yield on 10 year government Treasury bonds (10 year Treasury

are included in the calculation of Salomon Smith Barney’s market share.

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yield). In periods when interest rates are high, alternative sources of capital should be either scarce or

expensive. It is expected, therefore, that firms should be more likely to follow through on an IPO when

interest rates are high.

As a measure of relative valuation we include the industry average book-to-market ratio,

measured one year prior to the filing (industry average book-to-market).10 We have no strong prior

expectations regarding the effect of this variable on withdrawals. If book-to-market captures growth

opportunities, then the relationship should be positive (firms with more growth having lower book-to-

market ratios are less likely to withdraw11). On the other hand if book-to-market captures market

misvaluation, firms with low book-to-market ratios (overvalued firms) should be more likely to

withdrawal (it is more likely that firms will be detected as overvalued during the bookbuilding process).

To capture overall market sentiment leading up to the filing, we inc lude the return on the

Nasadaq composite index over 2 months pre filing. If information about firm valuation is correlated with

market movements, returns on the Nasdaq composite index should be negatively related to the likelihood

of withdrawal

All of the empirical measures discussed thus far are observable at the time of initial IPO filing. A

probit model estimated just with these variables, therefore, provides insights into the ex ante likelihood of

offering success. Information received after the filing date also should affect a firm’s decision to

withdrawal, however. We, therefore, include a number of variables to proxy for the information

environment after filing. Number of filings 2 months after filing and number of industry filings 2 months

after filing capture the IPO market intensity during bookbuilding. Predictions regarding the relationship

between these variables and withdrawals are similar to those for similar variables measured before

withdrawal. It should be noted that the two effects (information spillovers and limited capital) could have

different weight for these variables in the pre and post filing periods so it is possible to find different

relationships.

10 Obtained from Ken French’s web site (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html ) 11 The argument leading to this prediction is similar to that made for the high tech dummy variable .

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Changes to the interest rate environment are captured by in the change in BAA-AAA yield spread

2 months after filing and the change in 10-year Treasury yield 2 months after filing. If yield spreads are

an indicator of default probabilities, the likelihood of withdrawal should increase as the spread increases

post filing (a positive relationship). On the other hand, if yield spreads reflect access to alternative

sources of capital, withdrawals should be less likely as the spread increases (a negative relationship). If

the Treasury bond yield proxies for the costs and/or scarcity of alternative sources of capital, changes to

yields should be negatively related the likelihood of withdrawal.

Two final post-filing variables considered are the change in industry book-to-market ratio over

year of the filing (the book-to-market ratio at the end of the year of filing subtract the ratio at the

beginning of the year) and the return on the Nasdaq composite index over two months after filing. If

book-to-market captures growth opportunities, then changes to the industry ratio should be positively

related to the likelihood of withdrawal. On the other hand if book-to-market captures market

misvaluation, changes to book-to-market ratios should be positively related to the likelihood of

withdrawal. Finally, if information about firm valuation is correlated with market movements, returns on

the Nasdaq composite index post-filing should be negatively related to the likelihood of withdrawal

As a preliminary univariate investigation, we report descriptive statistics for the data items,

broken down by ultimate success of the offering in Table 2. Note that sample sizes change depending on

the variable examined. This reflects the fact that TFSD coverage of data items is extremely limited in

some cases (especially for withdrawn issues).

Withdrawn offerings have significantly lower average initial filing sizes ($59.12 million)

compared to completed offerings ($69.51 million). This is consistent with the prediction that more

speculative offerings are less likely to succeed. A greater percentage of high-tech firms are successful

than withdrawn (28% of completed offering are high tech whereas 24% of withdrawn offerings are high-

tech), consistent with the notion that withdrawals are more costly for high-tech firms. Firms with venture

capital backing a more likely to succeed (39% of completed IPOs have venture capital backing compared

to 13% of withdrawn IPOs). This is not consistent with venture capital backing proxying for capital

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constraints (those with venture capital backing presumably have greater access to alternative sources of

capital and, therefore, would be more likely to withdraw). It is consistent, however, with venture capital

backing acting as certification for the offering. 12 Withdrawn offerings are also more likely to have been

targeting for debt repayment (43% vs. 32%), consistent with predictions.

Successful offerings are more likely to be taken public by banks with greater reputations, proxied

by Carter-Manaster rankings (7.1 vs. 6.6), market share (4.3% vs. 1.9%) and industry market share

(14.5% vs. 2.7%), consistent with predictions.

Withdrawn IPOs are filed after periods with a greater average number of filings over the prior 2

months than completed offers (106.6 vs. 100.7), consistent with prior research. In addition, withdrawn

IPOs are filed after periods with greater numbers of industry filings (12.2 vs. 10.9). BAA-AAA yield

spreads are higher for successful offerings (0.84 vs. 0.81). This suggests that yield spreads are more

likely to be capturing access to capital than default probabilities. Treasury yields are not significantly

different for successful and unsuccessful offerings. Withdrawn offerings are more likely to be from

industries with lower book-to-market ratios (0.45 vs. 0.47), consistent with predictions from the

misvaluation theory (firms in lower market to book industries are more likely to be detected as

overvalued). The return on the Nasdaq composite index pre-filing is more positive for successful

offerings (4.1% vs. 2.9%), consistent with the notion that IPO firm valuations are correlated with overall

market valuations.

The relationships for variables measured after filing are generally consistent with those observed

pre-fling. The Nasdaq composite return post-filing is more positive for successful offerings (2.8% vs. -

1.2%). The change in Treasury yield is more negative (although not statistically) for withdrawn offers (-

0.048 vs. -0.028). The number of filings variables appear to have the opposite (or no) effect post filing.

This could be consistent with market intensity post-filing capturing market spillover effects more than

scarce capital effects. Finally, the effect of change in yield spreads is opposite to that predicted (the

12 Also, Gompers (1996) notes that venture capitalists have an incentive to bring firms early to the IPO market to capitalize their claims. This argument would suggest that venture capitalists would lobby hard for IPO completion.

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change is more positive for withdrawn offerings). As we will see, however, this finding does not hold up

in the multivariate analysis.

We formalize our univariate analysis of the determinants of IPO withdrawal in Table 3 using a

probit analysis. The dependent variable in the analysis takes the value 1 if the IPO filing is withdrawn

and 0 otherwise. We consider as independent variables all of the measures noted above. Table 3 reports

our probit model coefficient estimates and associated t-statistics. We also report the marginal effect for

each variable. Unlike ordinary least squares regressions, marginal effects, defined as the change in

probability of withdrawal given a one unit change in the independent variable, cannot be interpreted

through examination of the coefficient estimates. In a probit model, the marginal effect is defined as

φ(β�x)*β where φ() is the standard normal probability density function, β is the coefficient estimate and x

is the mean of the independent variable for the sample. To provide greater insight into the economic

impact of each variable we multiply this expression by σx, defined as one standard deviation for the

independent variable (σx is set to 1 for dummy variables). Our measure of marginal effect, therefore,

captures the change in the probability of withdrawal given a one standard deviation change in the

independent variable.

Our first probit model includes the all variables noted above except the use of proceeds variable

(the sample size drops when this variable is included so we consider that sample separately). Consistent

with the existing literature (see Busaba, Benveniste and Guo, 2001), we measure offering size using the

natural logarithm of the average filing size (logarithm of the filing size), to account for scale effects. In

unreported analyses, we replicate our findings using untransformed variables and find qualitatively

similar results.

Our analysis largely confirms the findings from the univariate analysis. The probability of

withdrawal is significantly positively related to the number of filings over the 2 months pre-filing, and the

change in industry market to book over the year of filing. The probability of withdrawal is negatively

related to the high tech industry dummy, the venture capital backing dummy, the investment bank overall

17

and industry market share, the average industry market to book ratio pre-filing, the number of filings post

filing and the return on the Nasdaq composite index post filing. Two variables have significantly

different relationships with withdrawals in the multivariate analysis. As noted above, the change in BAA-

AAA yield spread is negatively related to withdrawal likelihood. As spreads increase and access or cost

of alternative sources of capital become more problematic, firms are less likely to withdraw their IPO.

The relationship between withdrawals and the logarithm of filing size also is different in the multivariate

analysis. Larger offerings are more likely to be withdrawn, all else held equal. In the multivariate

analysis, it appears that other variables fully proxy for deal riskiness. All else equal, firms attempting to

raise more capital may have more alternative sources of capital or are simply more likely to be “caught”

attempting to raise too much money given market misvaluation (which get detected in the bookbuilding

process).

The most significant variable in the model, economically , is investment bank industry market

share. A one standard deviation increase in industry market share results in a 36% reduction in the

probability of withdrawal. The next most economically significant variables are venture capital backing

(venture capital backed IPOs are 14% less likely to be withdrawn), overall bank market share, logarithm

of filing size, BAA-AAA yield spread at filing, number of filings two months after filing and the return

on the Nasdaq composite index two months after filing (for each of these variables, one standard

deviation change in the variable results in an approximately 7% change in the probability of withdrawal).

The pseudo R2 for the model is 24%, suggesting the model does a good job explaining withdrawals.

The second probit model reported in Table 3 includes the use of proceeds variable. The sample

size drops significantly due to data limitations. The economic and statistical significance of most

variables previously considered are not altered in this smaller sample with two exceptions. The change in

10 year Treasury bonds after filing has a significant negative effect on the likelihood of withdrawal. The

Nasdaq composite return post filing now does not have a significant effect on the probability of

withdrawals. The new variable, use of proceeds, has a significantly positive effect on the probability of

withdrawal, consistent with the univariate analysis.

18

4. Withdrawn IPOs that Return to the Market

In this section we solely examine the sample of 1,485 withdrawn IPOs from 1985 to 2000. As

noted previously, 138 of these firm (or approximately 9%) return to the market for a successful IPO. We

first examine the average time difference between the unsuccessful issue date and the successful issue

date. Results are presented in Table 4. From panel A, the median (mean) time is 817 (658) days or 2.24

(1.80) years. The minimum is 125 days or 0.34 years, while the maximum 5,045 days or 13.82 years.

We also examine the probability of a successful re-issue based solely on the elapsed time since the

withdrawn issue date in panel B of Table 4. There is a 70 percent chance that a firm might still have a

successful issue about one year after a withdrawn issue, but only approximately a 25 percent chance after

about three years. If “market conditions,” often a stated reason for the postponement of new issues, are a

primary cause of the initial withdrawal, conditions should have improved within a few years at the latest.

However, it may well be that some firms cannot survive while waiting for market conditions to improve.

We next examine which factors most affect the probability of successful return. As discussed

previously, firms are less likely to withdraw an IPO if cancella tion can cause a “lemons” problem for the

issuing firm (Akerlof, 1970). Riskier firms that do withdraw should be less likely to be able to return

successfully in the future. Empirical measures considered previously as proxies for issuer and issue

riskiness should also be considered here (issue size, venture capital backing, high-tech industry status).

Firms with greater certification (taken forward initially by more reputable investment banks or having

venture capital backing) should face lower “lemons” concerns, increasing the likelihood of successful

return. Finally firms cancelling an IPO because they have access to other good sources of capital (proxied

by venture capital backing and use of proceeds) should be more likely to return (since “questions” about

firm quality should less significant).

Market conditions at the time of withdrawal should also impact a firm’s ability to return. Certain

variables have been argued to proxy for a firm’s access to alternative sources of capital. Firms

withdrawing when yield spreads and interest rates are low should be more likely to return (they get

19

interim capital and face less significant lemons concerns). Other market condition variables reflect

changing market sentiment, resulting in changing valuations. Firms withdrawing an IPO after a market

decline (or declining industry valuation ratios) are less likely to be able to return. Market intensity factors

are also likely to affect the likelihood of return. Firms that are unsuccessful because resources are scarce

should be less likely to return (not getting through initially sends a negative signal). Further, firms

cancelling an IPO in intense markets when information spillovers are more significant should be less

likely to return (these are the firms detected to be undesirable investments).

Finally, variables capturing market conditions after the withdrawal should affect the likelihood of

successful return.13 If valuations improve after filing (Nasdaq composite increases or industry book-to-

market decreases), firms should be more likely to emerge successfully. 14 Variables proxying for access to

alternative sources of capital should also be related to the probability of successful return. As sources of

capital dry up (yield spreads and treasury yields increase), those cancelling IPOs should turn back to the

market. Finally, IPO market intensity after withdrawal should impact the likelihood of successful

returning. The impact of market intensity on the likelihood of withdrawal is difficult to predict, however.

Under the scarce resource view, failed IPOs are less likely to be able to return if market intensity

increases as these issuers are competing for scarce capital. Under the information spillover view, greater

intensity may have positive valuation spillovers, increasing the likelihood of return.

As a preliminary univariate investigation, in Table 5 we report descriptive statistics for the data

items, broken down by whether the failed issuer is able to return for a successful IPO. Few of the

variables examined in Table 5 are significantly different for the sample of successful returners and the

sample of non-returners. Returners are significantly more likely to be venture capital backed (29% vs.

11%). The Carter-Manaster ranking is significantly higher for filers that return for a successful offerings

13 Unlike the prior analysis of withdrawal which measured ex post variables over a short (2 month) window, here returns are measured over a longer period (one year). This longer window is chosen to more closely match the typical time period between initial filing and possible return (see Table 4). In the analysis of withdrawals, the window was selected to match the typical registration period for successful and withdrawn offerings, which is shorter. 14 Often the stated reason for withdrawal is “adverse market conditions”. Presumably those firms that withdrew

20

(7.4) than filers that never return (6.5). The number of industry filings 2 months prior to withdrawal are

significantly lower for returning issuers (6.8 vs. 9.7). The return on the Nasdaq composite index 12

months after withdrawal is significantly higher for returning issuers (24% vs. 15%). All these findings

are consistent with predictions. The number of filings twelve months after withdrawal is greater for

returning firms (501 vs. 453), consistent with the spillover view of market intensity.

Two results are not consistent with predictions. First, the change in BAA-AAA yield spread post

withdrawal is significantly lower for returning issuers (-0.061 vs. -0.003). This finding does not hold up

in the multivariate analysis presented next, however. Second, industry market share is significantly lower

for firms that eventually return (1.16% vs. 2.91%). There are two possible explanations for this finding.

As we will see in upcoming analyses, returning firms often switch to banks with greater industry market

shares that are then more likely to successfully return. Further, industry market share could be considered

to be more a measure of market power than reputation (see Bates and Dunbar, 2002). Issuers

unsuccessful in their first attempt to go public even though they are taken forward by banks with more

market power are more likely to be “flawed”, and therefore less likely to return.

We formalize our analysis of the determinants of IPO return for withdrawn IPOs in Table 6 using

a multivariate probit analysis. The dependent variable in the analysis takes the value 1 if the withdrawn

IPO filing eventually returns for a successful offering and 0 otherwise. We report our probit model

coefficient estimates, marginal effects and associated t-statistics. The first model excludes the venture

capital dummy variable, resulting in a larger sample. The second model includes the venture capital

measure. Our analysis largely confirms the findings from the univariate analysis. Carter-Manaster

Ranking, venture capital backing and the number of filings 12 months after withdrawal have a positive

effect on the likelihood of successful return. Bank industry market share and number of industry filings 2

month prior to withdrawal have a negative impact on the likelihood of returning (the relationship in the

second case is only marginally significant, however). Some variables that were not significant in the

univariate analysis become signicant once controlling for other factors. The return on the Nasdaq

because things were bad will return once things improve.

21

composite index from filing to withdrawal has a negative effect on the probability of successful return.

The change in 10 year Treasury yield after withdrawal has a positive effect on the likelihood of successful

return. The 10 year Treasury yield at withdrawal has a positive effect on the likelihood of withdrawal.

These findings are consistent with predictions. The 10 year yield at withdrawal has a positive effect on

the likelihood of successful return, inconsistent with predictions. This could indicate that firm

withdrawing IPOs in spite of the high interest rate environment (when alternative sources of capital are

scarce or expensive) are higher quality and, therefore, more likely to re-emerge.

The most significant variables in this analysis, economically, are investment bank industry market

share, venture capital backing and the change in 10 year Treasury yields one year after withdrawal. A one

standard deviation increase in industry market share results in a 14% to 17% reduction in the probability

of successful return. Venture capital backed issuers are 21% more likely to successfully return. Finally, a

one standard deviation increase in 10 year Treasury yield post withdrawal results in a 12% increase in the

probability of successful return.

5. Investment Bank Switching for Returning Issuers

An interesting feature of the sample of successful reissuers is that in many (but not all) cases, the

issuing firm switches investment banks from the initial attempt to the final success. Two notable studies

examine the choice of a firm to switch investment banks from its IPO to a seasoned equity offering.

James (1992) examines the underwriter switching decision in the context of relationship-specific assets.

He argues that given high set-up costs (learning), firms would tend not to switch banks (so they can

amortize those costs over multiple offerings) unless performance by the bank on the IPO was poor.15

15 Recently Loughran and Ritter (2002a) present a prospect theory model to explain why issuers who see the overall value of their wealth increase at the time of an IPO may not be upset by underpricing. In his discussion of the paper, Daniel (2002) highlights the case of the Microsoft IPO whereby Bill Gates was concerned that a deliberate underpricing would simply benefit the lead underwriter’s favorite clients. While the Microsoft IPO was not withdrawn, one could speculate that a perception of deliberate underpricing could be an alternative explanation of why a firm might withdraw from the IPO and later return successfully with a different underwriter and with less

22

Consistent with this, James finds that pricing errors at the time of the IPO are significantly associated

with bank switches. Krigman, Shaw and Womack (2001) also examine the choice to switch underwriters.

In addition to the possibility that firms switch due to IPO mispricing, Krigman Shaw and Womack

consider a number of other explanations including poor share placement (resulting in high flipping),

limited market making activity, limited research coverage and graduation (simply moving to a bank with

greater reputation). They find evidence most consistent with the limited research coverage and

graduation explanations.

In the context of a previously withdrawn IPO, many of the explanations proposed by Krigman

Shaw and Womack (2001) simply cannot apply, including IPO mispricing, poor share placement, limited

market making and limited research coverage. All of those explanations require that the firm become

public. We consider the two remaining possibilities in our analysis. First, firms may switch investment

banks because a bank with a greater reputation is willing to underwrite the offering (the graduation

hypothesis). Second, firms may switch underwriters due to concerns with the initial investment bank’s

performance in the IPO process (the IPO performance hypothesis).

The graduation hypothesis is examined in Table 7. For each firm that switches we examine

measures of the reputation at the time of the successful offering for the bank used on the initial attempt

and the bank switched to. The graduation hypothesis predicts that switches occur in order to move up to

banks with greater reputation. In panel A of Table 7 we examine a sample of 98 cases where a firm

returns for their successful IPO with a different investment bank. At the time of the successful offering,

the original bank has an average Carter-Manaster rank of 7.3 whereas the bank switched to has an average

Carter-Manaster of 7.6. The difference between these two means is not significant. At the time of the

successful offering the original bank has an average market share of 3.6% whereas the bank switched to

has a market share of 4.9%. This difference again is not statistically significant. While these findings are

not consistent with graduation, the industry market share evidence is more supportive. At the time of the

successful offering the original bank has an average industry market share of 2.3% whereas the bank

underpricing.

23

switched to has an industry market share of 15.7%. The difference is significant at the 1% level. The

importance of industry market share supports evidence presented previously on factors affecting

withdrawal. In that analysis, industry market share was by far the most significant (economically)

determinant of offering success. After experiencing an IPO failure, issuers should attempt to change

banks to maximize their chance of success.

While not explored previously, several firms attempt to go public a second time and yet fail. In

panel B of Table 7 we examine a small sample of 15 issuers that attempted to go public a second time

with a new bank and failed. The Carter-Manaster ranking for the bank originally attempting to take the

firm public is 7.9 compared to 6.8 for the new bank. The difference is significant at the 10% level. This

suggests that the firms inability to obtain a more reputable bank on second attempt hurt its ability to

successfully complete its IPO. Industry market share is also lower for the new bank although differences

are not statistically significant. Market share increases after the switch although the new bank does not

arguably have a large average market share. Overall, this analysis suggests that the ability to attract a

more reputable bank on second attempt is an important determinant of offering success for reissuers.

In Table 8, we perform a similar analysis to give insight into the importance of the IPO

performance hypothesis. The measure of performance we consider is capital raised. Banks able to raise

more capital successfully for firms are arguably better performing intermediaries. In the first row of

Table 8 we report the mean IPO filing size on the first attempt for all returning issuers. We consider

separately cases where the issuers return for a successful IPO and cases where issuers return for a second

unsuccessful attempt. We also consider separately cases where the investment bank is changed and not

changed on second attempt for successful returners. Successful returners attempt to raise more capital on

the first attempt than unsuccessful returners (51 million vs. 28 million). Those successful returners who

switch attempt to raise significantly (at the 10 % level) less capital on the first attempt than those returners

who do not switch banks (44 million vs. 73 million). In the second row we report mean filing size on the

second attempt. Again, unsuccessful issuers attempt to raise much less capital than successful issuers (34

million vs. 65 million). On the second attempt, capital to be raised is no different for firms that switched

24

banks and firms that did not switch banks (66 million vs. 62 million). The percent change in offering size

is reported in the third row of the table. Unsuccessful issuers attempt to raise more capital on the second

attempt although the change is less than that for successful returners (32% vs. 107%).16 Successful

returners not changing banks attempt to raise about the same amount on second attempt (a 6% increase)

whereas successful returners switching banks raises substantially more on the second attempt (140%).

Differences in the rate of change are significant at the 5% level.

We interpret this evidence as being consistent with the IPO performance hypothesis. We

conjecture that banks switched away from attempted to raise “too little” on the failed attempt. The issuer

recognized this as poor performance and decided to switch to a bank that was able to raise more money

for the firm. Non-switchers initially attempted to raise an appropriate amount of money and on return

they were successful at that level. The issuer undoubtedly interpreted the first failure as the result of

factors beyond the bank’s control, like poor market conditions.

Changes in filing sizes may lead to confounding conclusions if switchers and non-switchers are

clustered in periods where “normal” changes to filing sizes differ. To account for this possibility we

define “abnormal” filing size as the difference between the filing size on this attempt and the average

filing size on all filings over the six months leading up to this attempt. The abnormal percent change in

filing size is then defined as the abnormal filing size on second attempt divided by the abnormal filing

size on first attempt, subtract one. Accounting for “normal” changes in filing size reduces the

significance (economically) of unadjusted findings but conclusions remain unchanged. The mean

abnormal percent change in filing size for successful returners having no bank change is -24% whereas

the mean abnormal percentage change in filing size for successful returners with a change in bank is

103%.

Overall, the evidence presented in this section thus far provides support for both the IPO

performance and graduation hypotheses. To provide additional insights we consider interactions between

16 Although the difference is not significantly different, power is likely to be an issue since there are so few firms in the sample of unsuccessful returners.

25

these hypotheses in Table 9. This table replicates the analysis in Table 8 for successful returners where

there is a change in bank but breaks down the evidence on filing size changes based on whether the bank

changed to has higher or lower measures of reputation. Generally, the percentage change in filing size

(and abnormal change in filing size) is larger when the bank switched to has a greater measure of

reputation. The effect is most significant when using industry market share as a measure of reputation.

We split the sample into two groups based on change to industry market share. Since most industry

market share changes are positive we use 2% as a cutoff in defining these two samples (we considered

other arbitrary cutoffs and found similar results). If the bank moved to has a much higher industry market

share, filing size increases by 173% whereas filing size increases only 15% if the new bank does not have

a significantly higher industry market share. The difference is significant at the 5% level. This suggests

that the graduation and performance hypotheses are complements. When dissatisfied with the

performance of their lead bank on first attempt, successful returners switch to banks with greater industry

presence who are able (due to their reputation and market power) to raise significantly more capital on

second attempt.

Overall, the evidence in this section indicates that IPO performance and graduation are both

important and complementary explanations for investment bank switching. The importance of IPO

performance is not consistent with the Krigman, Shaw and Womack’s (2001) evidence from a sample of

firms switching banks after a successful IPO. We believe our findings complement Krigman, Shaw and

Womack’s to give a broader impression of the importance of different roles played by investment banks

in the IPO process.

6. Likelihood of Return, Investment Bank Switching and the Choice to Withdraw an IPO

As documented previously, approximately 20% of all IPO filings are withdrawn prior to

completion. Of those withdrawals, only 10% manage to return for a successful offering. If going public

through an IPO was an important part of a company’s strategy for long-term success, it is reasonable to

26

expect that most firms canceling an IPO hope to return. All else equal, we would therefore expect that the

probability of successful return should be an important factor in a firm’s choice to withdraw its IPO.

Issuer’s more likely to return should be more likely to withdraw.

To examine this hypothesis, we first estimate a probit model of withdrawals for all IPO filings.

To do this we start with the models estimated in Table 6. We do not use the full models reported in Table

6 since many of the variables used to estimate the probability of return are not known until after the filing

is withdrawn. We would like to estimate a model of successful returning using variables that are known

at the point when the firm faces the decision to withdraw or proceed with the IPO. We, therefore,

estimate models like those in Table 6 excluding the market conditions after withdrawal variables. These

models are then used to estimate the probability of successful return for all issuers.17 This variable is then

added to the list of independent variables considered previously in Table 3 to predict withdrawal. Again,

since we are trying to estimate a probability model for withdrawal as of the time of withdrawal, market

condition variables are defined at that point.

The results are presented in Table 10. As done previously, we report probit estimates, t-statistics

and marginal effects for the model. The effects of various variables previously considered on

withdrawals are similar (in sign, economic and statistic significance) to that reported previously. 18 The

probability of successful return variable is significantly positive, as expected. A one standard deviation

increase in the likelihood of successful return results in a 7% increase in the probability of withdrawal,

making this variable among the most economically significant variables in the model.

The analysis in the previous section showed that investment bank switching was prevalent for

firms returning to the market after a failed attempt. It was also noted that not all second time issuers

succeed on the second attempt. In Table 7, we showed that second time successful filers tended to move

17 Specifically, the probability of return is Φ(βx), where x is a vector of independent variables, β is a vector of probit estimates and Φ() is the standard cumulative normal distribution function. 18 The market condition variables at time of withdrawal are not comparable to findings in Table 3 since the time periods over which variables are measured are not the same. These variables are measured post filing, however, so they are more comparable to the market conditions after filing variables considered previously. These comparisons suggest the effects of variables are similar in the two analyses.

27

to banks with substantially greater industry market shares than second time unsuccessful filers. We

formally examine the relationship between withdrawal on a second attempt and investment bank

switching by estimating a probit model of withdrawal for second time filers. Given the relatively small

sample size we attempt to develop a parsimonious base model using independent variables considered

previously. In Table 10 we report a model using variables that are most significant (economically or

statistically). The effects of various independent variables on withdrawal are similar to that for the full

sample of first second time filers, although statistical significance is reduced in most cases. Two new

variables are added to the model to capture the effects of investment bank switching. The first is a

dummy variable equal to one if there is a bank switch. The second is a variable equal to the change in

industry market share (measured at the time of the filing on the second attempt) from first to second bank

(if there is no bank change, this variable is set to zero, so it can be considered an interactive variable with

the bank change dummy).19

The change in bank dummy variable has a significantly positive effect on withdrawals. The

change in industry market share variable has a significantly negative effect. Second time unsuccessful

filers are more likely to switch but (as noted previous) tend to switch to banks with less significant

industry presence. This suggests that these are firms that are rejected by their initial bank and

unsuccessful in their attempt to find a more prominent bank to take them public. Successful second time

filers switch banks only if they can attract a bank with significantly greater industry stature which

increases their chance of success.

7. Withdrawals, Returners, and the Pricing of IPOs

In this section we examine the pricing of successful IPOs from 1985 to 2000. Specifically, we

examine price adjustments made during the bookbuilding process and first day returns (underpricing) for

19 We considered other measures to capture the change in Carter-Manaster ranking and overall bank market share but these variables were not significant.

28

successful IPOs. We examine whether the likelihood of withdrawal and possibility of successful return

affects pricing behaviour for successful offerings. Busaba, Benveniste and Guo (2001) present a model

where issuers can use to threat of withdrawal as leverage with investors in the bookbuilding process to

illicit truthful information. In their model, firms more likely to withdraw need not underprice as severely

in response to positive information. Their model also indicates that initial returns should be unrelated to

the probability of withdrawal in cases where negative information is revealed through bookbuilding. No

prediction emerges from the model with respect to the effect of the probability of withdrawals on price

adjustments. We posit that firms more likely to withdraw who also face a lower probability of successful

return are more likely to cut prices in an attempt to assure success on first attempt. Price adjustments,

therefore, should be more negative, all else equal, for these issuers. Relatedly, first day returns could be

more positive for these firms if price cutting is deeper than necessary to ensure the offering is successful.

To test these predictions, we first estimate ordinary least square models of price adjustments.

Hanley (1993) presented the first analysis of price adjustments made between the initial filing of

regulatory documents with the SEC and the approval of the offering when the bank sets a final price. She

argued that price adjustments proxy for information acquired during bookbuilding. When information

revealed is positive, price revisions are positive and when information revealed is negative, price

revisions are negative. To model price adjustments, she regressed adjustments on proxies for information

revelation. She found, for example, that price adjustments are positively related to market returns during

the filing process. When market returns are positive, information revealed about a given IPO is also

likely to be positive. She also found that price adjustments are positively related to investment bank

reputation proxies. More reputable banks are more likely to uncover positive information.

More recently, Benveniste, Ljungqvist, Wilhelm and Yu (2003) examine price adjustments and

argue that price adjustments should be related to proxies for information spillovers (from both market

factors and more industry related measures). They also argue that argue that price adjustments should be

related to deal and market riskiness (information is more likely to be uncovered in more speculative

offerings and in more risky periods). Our model of price revision, therefore, includes fairly standard

29

measures of deal riskiness including overhang20, venture capital backing (a variable taking the value 1 if

the IPO is venture capital backed as indicated by TFSD and 0 otherwise; see Barry, Muscarella and

Vetsuypens, 1990, and Megginson and Weiss, 1991), exchange listing (NYSE which is a dummy variable

taking the value 1 if the IPO list on the New York Stock Exchange and AMEX which equals one if the

IPO lists on the American Stock Exchange; see Lowry and Schwert, 2002) and firm standard deviation

(the standard deviation of stock returns from days +21 to +50 relative to the IPO; see Johnson and Miller,

1988, Carter Dark and Singh, 1998, and Lowry and Schwert, 2002). We also include Market Standard

Deviation (the standard deviation of daily returns from day -50 to -2 relative to the IPO on the CRSP

value weighted index) as a measure of market risk. Consistent with the previous research we include

Carter-Manaster ranking as a measure of investment bank reputation.

We also control for variables likely to be associated with information spillovers in our

regressions. Market Return, defined as the compound return from day –50 to –2 relative to the IPO on the

CRSP value weighted index, is included as an independent variable in our analysis.21 To allow for non-

linearities in the relation between market returns and price adjustment, we also include Market Return +

as an independent variable where Market Return + takes the same value as Market Return whenever it is

positive, and 0 otherwise (see Loughran and Ritter, 2002b, and Lowry and Schwert, 2002). As an

additional measure of pre-IPO market activity (and information spillovers) we include Number of Prior

IPOs, the number of IPOs from days –60 to –1 relative to the offering, and Number of Prior Industry

IPOs, the number of industry IPOs over the same period in our regressions (see Booth and Chua, 1996,

and Benveniste, Ljungqvist, Wilhelm and Yu, 2002).

To examine the impact of withdrawals and the potential to return on price adjustments we

construct a dummy variable which takes the value 1 if the issuer has a high ex ante probability of

20 Overhang is number of shares outstanding after the IPO net of the number of shares offered in the IPO all divided by the number of shares offered in the IPO. The number of shares in the IPO is obtained from TFSD and includes global tranches but exclude the overallotment option. Overhang can be thought of as a liquidity measure but also captures insider retention. Both are related to deal riskiness (see Bradley and Jordan, 2002). 21 The specification for the market return in this regression is chosen to match that used by Lowry and Schwert (2002).

30

withdrawing and a low ex ante chance of returning. Specifically, predicted probabilities of withdrawal

and returning are estimated using the ex ante probit models discussed in section 6. The dummy variable

HW-LR is set to 1 if the probability of withdrawal exceeds 2% and the probability of returning is less than

13% (these are the mean numbers in sample).

The ordinary least square estimates are reported in Table 11. The dependent variable, price

adjustment, is defined as the final offering price minus the average of the high and low initial filing prices

all divided by the average of the high and low initial filing prices. Consistent with prior research, venture

capital backed offerings and those underwritten by banks with higher Carter-Manaster ranks tend to have

more positive price adjustments during the bookbuilding process. Overhang is positively related to price

adjustments, as found by Bradley and Jordan (2002). Price adjustments are also more positive for riskier

offerings (proxied by firm standard deviation of returns) and when market and industry information

spillovers are likely to be positive (proxied by the market return and the number of prior industry IPOs).

Consistent with predictions, the dummy variable HW-LR, reflecting chance of withdrawal and

return, is negatively related to price adjustments. All else equal, issuers are more likely to cut their

offering price if they believe (as of the time of issue of withdrawal) that they have a strong chance of

failing and little chance of getting a second opportunity.

To examine the impact of withdrawal and return probabilities on IPO initial returns, we estimate

ordinary least square initial return regressions. The dependent variable, IPO initial return, is defined as:

100*(P1st day close – Poffer)/Poffer, where P1st day close is the closing price at the end of the first-day of trading and

Poffer is the offering price from TFSD. Control variables are motivated based on the existing literature.

All the independent variables used to explain price adjustments are also included here, including

Overhang (Bradley and Jordan, 2002), Venture Capital Backing (see Barry, Muscarella and Vetsuypens,

1990, and Megginson and Weiss, 1991) , NYSE dummy and AMEX dummy (Lowry and Schwert, 2002),

Firm Standard Deviation (see Johnson and Miller, 1988, Carter Dark and Singh, 1998, and Lowry and

Schwert, 2002), Carter and Manaster Ranking , Market Return, and Market Return + (see Loughran and

Ritter, 2002b, and Lowry and Schwert, 2002), Market Standard Deviation, Number of Prior IPOs and

31

Number of Prior industry IPOs (see Booth and Chua, 1996, and Benveniste, Ljungqvist, Wilhelm and Yu,

2002).

As an additional measure of pre-IPO market activity we include Lagged Average Underpricing,

the mean first-day returns on all IPOs on days –60 to –1 relative to the offering, as an independent

variable (see Loughran and Ritter, 2002b, Lowry and Schwert, 2002, and Bradley and Jordan, 2002).

Finally, we include two independent variables to capture the relationship between information revelation

and first day returns. Price Adjustment, the dependent variable in the regressions discussed above is one

variable. The other, Price Adjustment +, takes the same value as Price Adjustment when Price

Adjustment is positive and 0 otherwise. This specification allows for an asymmetric relationship between

price adjustments and initial returns (Lowry and Schwert, 2002, Bradley and Jordan, 2002, Ljungqvist

and Wilhelm, 2002a and Ljungqvist and Wilhelm, 2002b). In Benveniste and Spindt’s (1989) formal

partial adjustment model, investment banks attempt to obtain private information from regular “informed”

investors about the value of the securities in an IPO prior to setting the final offering terms (during the

“bookbuilding” process). To induce truthful revelation when information is positive, the bank

precommits to allocate shares at a value below that revealed to those indicating the positive information.

No such incentive is required, however, to get investors to reveal negative information. Initial returns are

only significantly positive when positive information is revealed, result ing in an asymmetric relation.

As in the price adjustment regression we include the dummy variable HW-LR to capture the ex

ante chance of IPO success and chance of return if unsuccessful. In addition, we interact this dummy

variable with the price adjustment variables. The Busaba, Benveniste and Guo (2001) theory argues that

the possibility of withdrawal gives issues the leverage to reduce underpricing only when positive

information is revealed. This suggests that the interactive variable HW-LR * Price Adjustment + should

be significantly negative. Initial returns given negative information should be no different for firms more

likely to withdraw and those less likely to withdraw. Thus, their theory predicts that HW-LR * Price

Adjustment should be insignificant. As noted previously, we posit that price cuts may be deeper than

necessary for firms more likely to withdraw and less likely to return to ensure success. In this view, HW-

32

LR * Price Adjustment would be significantly negatively related to init ial returns (the more negative the

price adjustment, and therefore this variable, the more positive the first day return).

The initial return regressions are reported in Table 11. The relationship between control variables

and initial returns is consistent with the prior literature. Overhang, firm standard deviation, market

standard deviation, lagged IPO underpricing and the price adjustment variables have a positive impact on

initial returns. NYSE and AMEX listing and Carter-Manaster ranking have a negative impact on initial

returns. The regression results also confirm findings from Busaba, Benveniste and Guo (2001) with

respect to withdrawal likelihood. Only HW-LR * Price adjustment + is statistically significant. Its

negative coefficient indicates that initial returns are lower given positive price adjustments if the offering

is likely to be withdrawn and has a low chance of returning.

The regressions indicate that offerings more likely to be withdrawn and less likely to be able to

return have more negative price adjustments but these more negative price adjustments do not translate to

more positive initial returns. In other words, issuers are not cutting price “more than normal” resulting in

larger first day returns. This result, together with the finding that price revisions are more negative for

these firms, indicates that the initial pricing for these issues was simply too aggressive. This is consistent

with the prior finding that the probability of withdrawal is positively related to filing size.

The sample of successful IPOs examined in Table 11 includes first time issuers and some that

are successful on their second attempt. We add additional variables to our regressions to see whether

IPO pricing is different for second time issuers. In the context of a previously withdrawn IPOs, we

would expect price adjustment behavior to be different than that observed for “first time” issuers.

Specifically, we expect price adjustments to be less positive , all else equal, for two reasons. First,

issuers would be more averse to failure and, therefore, willing to leave more “money on the table” to

ensure success. In the face of positive valuation information revealed in the premarket, issuers would

not respond by adjusting price as significantly as first-time issuers. Second, return issuers would be

perceived as more risky by investors (given the “lemons” problem referred to previously).

33

Benveniste and Spindt (1989) argue that price adjustments should be lower (and first day returns

higher) for speculative offers since information is more costly to acquire (and more valuable) so

investors need greater returns to induce truth telling.

In the first price adjustment regression of Table 11 we add a dummy variable which takes the

value 1 if the IPO was previously withdrawn. This variable is negative, consistent with expectations,

but not significant. In the second price adjustment regression of Table 11, we add two dummy

variables. The first takes the value 1 if the offering was previously withdrawn and brought forward

by the same bank that helped the firm make the initial attempt. The second takes the value 1 if the

offering was previously withdrawn and brought forward by a new bank. We have no strong prior

beliefs about which group should have more negative price adjustments. If a firm uses the same

bank, that bank may be very nervous about failing twice and therefore would be more likely to

aggressively cut prices. Also, those firms attracting new banks may benefit from the renewed

certification that comes from being able to attract a new intermediary. This suggests that price

cutting may be deeper if there is no change in bank. On the other, the evidence reported previously

indicates that the initial filing size for second time issuers experiences a larger jump than observed

for issuers that don’t change banks. The new banks may have been overly aggressive in their

attempt to win the business and, therefore, are more likely to have to reduce prices during the

offering process.

The evidence in Table 11 is more consistent with the second story. Price adjustments are

significantly negative if the offering was previously withdrawn and now brought forward by a

different bank (at the 10% level). Price adjustments are not significantly unusual controlling for

other factors, however, if there is no bank change.

We also examine initial returns for second time issuers in Table 11. If negative price

adjustments are due to negative information revelation, initial returns should be lower for previously

withdrawn issuers. On the other hand, if price cutting is done to ensure offering success, we could

34

observe more positive returns for previously withdrawn offerings. The evidence is more consistent

with this second story. In the first initial return regression of Table 11 we include the dummy

variable which takes the value 1 if the IPO was previously withdrawn. This variable is not

significant, which is consistent with the first reported price adjustment regression which shows no

significant relationship between prior withdrawals and price adjustments. In the second initial return

regression, the coefficient on the dummy variable which takes the value 1 if the offering was

previously withdrawn and brought forward by a new bank is significantly negative. Together with

the price adjustment regression, this suggests that second time issuers with new banks cut prices

unusually to ensure offering success. The price cuts are more than needed and, as a result, initial

returns are more positive.

8. Conclusions

In this study we add to our understanding of the choice to withdraw an IPO. This choice is

puzzling since so few firms ever return to the market for a successful IPO. We study returning issuers

and find that firm’s initially brought forward by more reputable investment banks, and those having

venture capital backing are more likely to return. In other words, issues that have more ex ante

certification have a better chance of surviving the negative event of a withdrawal. Market conditions at

the time of the withdrawal and afterwards also have an impact on an issuer’s ability to return. Issues

withdrawn in more active IPO markets, when interest rates are high and when market returns are low are

more likely to be able to return.

Since the likelihood of returning is predictable, we examine whether this likelihood affects the

firm’s choice to withdraw. We find that the probability of withdrawal is positively related to the

likelihood of successful return. Issuers that face the choice to withdraw but do not expect to get a second

chance are more likely to try to push forward and complete their IPO. The likelihood of withdrawal and

35

possibility of return also has an impact the pricing of successful IPOs. In order to ensure success, firms

expected to withdrawal with a low chance of returning cut prices during the bookbuilding process.

Overall, the evidence in this paper indicates that firms consider the costs of withdrawal when

attempting to decide whether or not to proceed with an IPO. Firms not likely to get a second chance are

more likely to push forward, even though this might require that the issuer more substantially cut prices

than would be expected.

Our sample of previously withdrawn IPOs also provides a unique context in which to investigate

underwriter switching after a withdrawal but before a successful IPO, complementing the existing

literature on switching after a successful IPO but before a subsequent equity offering. We find that

issuers “graduate” to banks having larger industry market shares when they deem that their initial bank

did not perform well on first attempt (they attempted a small offering and did not succeed). This evidence

provides a more balanced view on the role of graduation and performance than previous research which

diminished the importance of the performance story but examined cases where performance was arguably

good. This study, therefore, also provides insights into the role played by investment banks in the process

of raising capital through an IPO.

References Akerlof, G., 1970, The market for ‘lemons’: Quality and the market mechanism, Quarterly Journal of Economics 84, 488-500. Baron, David P., 1982, A model of the demand for investment banking advising and distribution services for new issues, Journal of Finance 37, 955-976. Barry, C., C. Muscarella , J. Peavy, and M. Vetsuypens, 1990, The role of venture capital in the creation of public companies: Evidence from the going public process. Journal of Financial Economics 27, 447-471. Bates, T. and C. Dunbar, 2002, Investment Bank Reputation, Market Power, and the Pricing and Performance of IPOs, Unpublished working paper, University of Delaware and University of Western Ontario. Beatty, R. and J. Ritter, 1986, Investment banking, reputation, and the underpricing of initial public offerings, Journal of Financial Economics, 15, 213-232. Benveniste, Lawrence M, Alexander P. Ljungqvist, William J. Wilhelm and Xiaoyun Yu, 2002, Evidence of Information Spillovers in the Production of Investment Banking Services, Journal of Finance, forthcoming. Benveniste, L. and Spindt, P., 1989, How investment bankers determine the offer price and allocation of new issues, Journal of Financial Economics, 24, 343-361. Booth, J., Chua, L., 1996, Ownership dispersion, costly information, and IPO underpricing. Journal of Financial Economics 41, 291-310. Booth, J., Smith, R., 1986, Capital raising, underwriting and the certification process. Journal of Financial Economics 15, 261-281. Bradley, Daniel and Brad Jordan, 2002, Partial adjustment to public information and IPO underpricing, Journal of Financial and Quantitative Analysis forthcoming. Busaba, Walid, L. Benveniste and R-J Guo, 2001, The option to withdraw IPOs during the premarket: empirical analysis, Journal of Financial Economics 60, 73-102 Carter, R., F. Dark and A. Singh, 1998, Underwriter reputation, initial returns, and the long-run performance of IPO stocks, Journal of Finance, 53, 285-311. Carter, R. and S. Manaster, 1990, Initial public offerings and underwriter reputation, Journal of Finance, 45, 1045-1067. Cho, Sung-Il, 1992, The possibility of failure and the pricing of best-efforts initial public offerings, Quarterly Review of Economics and Finance, 31-2, 30-45. Clarke, Jonathan, Craig Dunbar and Kathleen Kahle, 2001, Long-run performance and insider trading in completed and canceled seasoned equity offerings, Journal of Financial and Quantitative Analysis 36, 415-430.

Daniel, Kent, 2002, Discussion of “Why don’t issuers get upset about leaving money on the table in IPOs?”, Review of Financial Studies, 15, 445-454. Dunbar, Craig, 1998, The Choice between Firm-Commitment and Best-Efforts Offering Methods in IPOs: The Effect of Unsuccessful Offers, Journal of Financial Intermediation, 7, 60-90. Dunbar, Craig, 2000, Factors Affecting Investment Bank Initial Public Offering Market Share, Journal of Financial Economics, 55, 3-41. Fama, Eugene and Ken French, 1997, Industry costs of equity, Journal of Financial Economics, 43, 153-193. Gompers, Paul, 1996, Grandstanding in the venture capital industry, Journal of Financial Economics, 42, 133- 156. Grinblatt, Mark and Chuan Yang Hwang, 1989, Signalling And The Pricing Of New Issues, Journal of Finance 44, 393-420 Hanley, Kathleen Weiss, 1993, The underpricing of initial public offerings and the partial adjustment phenomenon, Journal of Financial Economics 34, 231-250. James, C., 1992, Relationship-specific assets and the pricing of underwriter services, Journal of Finance, 47, 1865-1885. Johnson, J. and R. Miller, 1988, Investment banker prestige and the underpricing of initial public offerings, Financial Management 17, 19-29. Krigman, Laurie, Wayne Shaw and Kent Womack, 1999, The persistence of IPO mispricing and the predictive power of flipping, Journal of Finance, 54, 1015-1044. Krigman, Laurie, Wayne Shaw and Kent Womack, 2001, Why do firms switch underwriters?, Journal of Financial Economics, 60, 245-284. Lerner, Josh, 1994, Venture Capitalists and the Decision to Go Public, Journal of Financial Economics, 35, 293-316. Ljungqvist, Alexander P. and William J. Wilhelm, 2002a, IPO Pricing in the Dot-Com Bubble: Complacency or Incentives?, Journal of Finance, forthcoming. Ljungqvist, Alexander P. and William J. Wilhelm, 2002b, IPO Allocations: Discriminatory or Discretionary?, Journal of Financial Economics, forthcoming. Loughran, Tim and Jay Ritter, 1995, The new issues puzzle, Journal of Finance 50, 23-51. Loughran, Tim and Jay Ritter, 2002a, Why don’t issuers get upset about leaving money on the table in IPOs?, Review of Financial Studies, 15, 413-443. Loughran, Tim and Jay Ritter, 2002b, Why has IPO underpricing changed over time?, Unpublished working paper, University of Florida and Notre Dame University.

Lowry, Michelle and G. William Schwert, 2002, Biases in the IPO Pricing Process, Unpublished working paper, Penn State University and University of Rochester. Megginson, William and Kathleen Weiss, 1991, Venture capitalist certification in initial public offerings, Journal of Finance 46, 879-903. Mikkelson, Wayne and M. Megan Partch, 1988, Withdrawn security offerings, Journal of Financial and Quantitative Analysis 23, 119-133. Ritter, Jay R., 1987, The costs of going public, Journal of Financial Economics, 19, 269-281. Ritter, Jay R., 1991, The long-run performance of initial public offerings, Journal of Finance, 46, 3-27. Rock, Kevin, 1986, Why new issues are underpriced, Journal of Financial Economics 15, 187-212. Seguin, P. and M. Smoller, 1997, Share price and mortality: An empirical evaluation of newly listed Nasdaq stocks, Journal of Financial Economics, 45, 333-363. Titman, S. and R Wessels, 1988, The determinants of capital structure choice, Journal of Finance, 53,1935-1974. Welch, Ivo, 1992, Sequential sales, learning, and cascades, Journal of Finance, 47, 695-732.

Table 1 IPO Filings Number of IPO filings from 1985 to 2000. The sample is obtained from the Thomson Financial Securities Data (TFSD) database. Issues that are unit offerings, REITs, ADRs or closed-end funds are excluded.

Year of filing

Number of IPOs filed

in year

Number filed in year that are withdrawn

Number filed in year that are withdrawn

then return for successful IPO

Percentage of filings that are

withdrawn

Percentage of withdrawn

offerings that return for a

successful IPO1985 298 37 1 12.42 2.701986 665 92 7 13.83 7.611987 448 95 14 21.21 14.741988 185 35 3 18.92 8.571989 154 15 1 9.74 6.671990 171 35 5 20.47 14.291991 394 35 4 8.88 11.431992 507 104 18 20.51 17.311993 623 83 14 13.32 16.871994 504 116 16 23.02 13.791995 564 54 8 9.57 14.811996 824 128 17 15.53 13.281997 569 113 6 19.86 5.311998 405 131 21 32.35 16.031999 592 102 2 17.23 1.962000 539 298 1 55.29 0.34

Total 7442 1473 138 19.79 9.37

Table 2 Descriptive Statistics – Successful and Withdrawn IPOs This table reports sample means (mean) and number of observations (obs) for different variables broken down by whether the IPO filing is successful or withdrawn. Issuer and issue characteristic variables are defined as follows. Average filing price is the average of the high and low price indicated in the initial filing. Filing size equals the average filing price multiplied by the number of shares to be sold as indicated in the initial filing (reported in January 2000 dollars using the CPI as a deflator). High-tech industry dummy takes the value 1 if the issuer is in Fama -French industries 34 (business services) or 36 (chips) and 0 otherwise (see Fama and French, 1997). Venture capital backing dummy takes the value 1 if the issuing firm has received venture capital investments prior to filing and 0 otherwise. Use of proceeds dummy takes the value 1 if the primary stated use of proceeds is retirement of debt. Debt to assets ratio is total debt pre filing divided by total assets pre filing. Investment bank characteristic variables are defined as follows. Carter-Manaster Rank is the Carter-Manaster (1990) ranking on a 0-9 scale for the book manager of the IPO (the maximum rank if there is more than one book manager). Bank market share is the sum of gross proceeds (not including the overallotment option) over the year prior to the IPO of all offerings where the IPO book manager is the book manager (equal credit given if there is more than one manager) divided by the sum of gross proceeds on all IPOs over the same period. Bank industry market share is the sum of gross proceeds over the year prior to the IPO of all IPOs in the same Fama-French industry where the IPO book manager is the book manager divided by the sum of gross proceeds on all industry IPOs over the same period. Market condition variables at the time of the filing are defined as follows: Number of filings prior 2 months is the number of IPOs filed with the SEC during the 2 months prio r to the filing date for the IPO. Number of industry filings prior 2 months the number of IPOs in the same Fama -French industry filed with the SEC during the 2 months prior to the filing date for the IPO. BAA-AAA yield spread at time of filing is the spread between BAA and AAA corporate bonds (from Moody’s) on the day of the filing. 10-year Treasury yield at filing is the average yield on US Treasury bonds having 10 years to maturity measured on the day of the filing. Industry average book-to-market pre filing is the book to market ratio for firms in the IPO issuer’s Fama-French industry at the end of the year prior to filing (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html). Change in industry BM over year pre filing is the change in the IPO industry book-to-market ratio over the calendar year ending prior to the filing. Return on Nasdaq Composite Index 2 months pre filing is the compound return on the index over two months ending the filing date. Market condition variables after the offering are defined s follows. Number of filings 2 months after the filing is the number of IPOs filed with the SEC during the 2 months after the filing date for the IPO. Number of industry filings 2 months after the filing is the number of IPOs in the same Fama -French industry filed with the SEC during the 2 months after the filing date for the IPO. Change in BAA-AAA yield spread 2 month after filing is the BAA-AAA yield spread two months after the filing date subtract the yield spread on the filing date. Change in 10-year Treasury yield 2 months after filing is the 10-year Treasury yield two months after the filing date subtract the 10-year Treasury yield on the filing date. Return on Nasdaq Composite Index 2 months after filing is the compound return on the index over two months beginning the filing date.

Successful Withdrawn

p-values (from t-test) successful vs. withdrawn

mean obs mean obs Issuer and issue characteristics Average filing price 13.884 5538 15.143 1076 0.392 Filing size 69.510 5538 59.118 1076 0.025 High-tech industry dummy 0.276 5538 0.241 1076 0.014 Venture Capital backing dummy 0.388 5538 0.134 746 0.000 Use of proceeds dummy 0.317 5338 0.428 306 0.000

Table 2, continued Descriptive Statistics – Successful and Withdrawn IPOs

Successful Withdrawn

p-values (from t-test) successful vs. withdrawn

mean obs mean obs Investment bank characteristics Carter-Manaster rank 7.069 5538 6.625 1076 0.000 Bank market share 4.330 5538 1.881 1076 0.000 Bank industry market share 14.453 5538 2.715 1076 0.000 Market conditions at time of filing Number of filings prior 2 months 100.650 5538 106.550 1076 0.000 Number of industry filings prior 2 months 10.948 5538 12.204 1076 0.053 BAA-AAA yield spread at filing 0.836 5538 0.810 1076 0.001 10-year Treasury yield at filing 6.872 5538 6.843 1076 0.475 Industry average book-to-market pre filing 0.474 5538 0.451 1076 0.007 Change in industry BM over year pre filing -0.043 5538 -0.040 1076 0.396 Return on Nasdaq Composite Index 2 months pre filing 0.041 5538 0.029 1076 0.000 Market conditions after the filing Number of filings 2 months after filing 102.750 5538 100.490 1076 0.125 Number of industry filings 2 months after filing 11.265 5538 11.765 1076 0.454 Change in BAA-AAA yield spread 2 month after filing -0.003 5538 0.013 1076 0.000 Change in 10-year Treasury yield 2 months after filing -0.028 5538 -0.048 1076 0.195 Return on Nasdaq Composite Index 2 months after filing 0.028 5538 -0.012 1076 0.000

Table 3 Probit analysis of the decision to withdraw an IPO for IPO filings between 1985 and 2000 The dependent variable equals one for IPO filings that are withdrawn and zero for completed offerings. Independent variables are defined as follows. Issuer and issue characteristic variables are defined as follows. High-tech industry dummy takes the value 1 if the issuer is in Fama -French industries 34 (business services) or 36 (chips) and 0 otherwise (see Fama and French, 1997). Logarithm of the filing size equals the natural logarithm of the average filing price multiplied by the number of shares to be sold as indicated in the initial filing (reported in January 2000 dollars using the CPI as a deflator). Venture capital backing dummy takes the value 1 if the issuing firm has received venture capital investments prior to filing and 0 otherwise. Use of proceeds dummy takes the value 1 if the primary stated use of proceeds is retirement of debt. Debt to assets ratio is total debt pre filing divided by total assets pre filing. Investment bank characteristic variables are defined as follows. Carter-Manaster Rank is the Carter-Manaster (1990) ranking on a 0-9 scale for the book manager of the IPO (the maximum rank if there is more than one book manager). Bank market share is the sum of gross proceeds (not including the overallotment option) over the year prior to the IPO of all offerings where the IPO book manager is the book manager (equal credit given if there is more than one manager) divided by the sum of gross proceeds on all IPOs over the same period. Bank industry market share is the sum of gross proceeds over the year prior to the IPO of all IPOs in the same Fama-French industry where the IPO book manager is the book manager divided by the sum of gross proceeds on all industry IPOs over the same period. Market condition variables at the time of the filing are defined as follows: Number of filings prior 2 months is the number of IPOs filed with the SEC during the 2 months prior to the filing date for the IPO. Number of industry filings prior 2 months is the number of IPOs in the same Fama -French industry filed with the SEC during the 2 months prior to the filing date for the IPO. BAA-AAA yield spread at time of filing is the spread between BAA and AAA corporate bonds (from Moody’s) on the day of the filing. 10-year Treasury yield at filing is the average yield on US Treasury bonds having 10 years to maturity measured on the day of the filing. Industry average book-to-market pre filing is the book to market ratio for firms in the IPO issuer’s Fama-French industry at the end of the year prior to filing (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html). Market condition variables after the offering are defined s follows. Number of filings 2 months after the filing is the number of IPOs filed with the SEC during the 2 months after the filing date for the IPO. Number of industry filings 2 months after the filing is the number of IPOs in the same Fama-French industry filed with the SEC during the 2 months after the filing date for the IPO. Change in BAA-AAA yield spread 2 month after filing is the BAA-AAA yield spread two months after the filing date subtract the yield spread on the filing date. Change in 10-year Treasury yield 2 months after filing is the 10-year Treasury yield two months after the filing date subtract the 10-year Treasury yield on the filing date. Return on Nasdaq Composite Index 2 months after filing is the compound return on the index over two months beginning the filing date. Change in industry BM over year of filing is the industry average book-to-market ratio at the end of the filing year subtract the average ratio at the beginning of the filing year. Marginal effect is defined as φ(β�x)*β*σx where φ() is the standard normal probability density function, β is the coefficient estimate, x is the mean of the independent variable for the sample and σx is one standard deviation for the independent variable (σx is set to 1 for dummy variables). Pseudo R2 is defined as 1 subtract the log likelihood for the estimated model divided by the log-likelihood for a model with only an intercept as an independent variable.

Table 3, continued Probit analysis of the decision to withdraw an IPO for IPO filings between 1985 and 2000

Coefficient Marginal

effect t-stat Coefficient Marginal

effect t-stat

Intercept -0.049 -0.019 -0.19 6.187 0.000 6.62 Issuer and issue characteristics High-tech industry dummy -0.257 -0.045 -3.27 -0.721 -0.282 -4.07 Logarithm of the filing size 0.304 0.073 8.40 0.353 0.069 4.41 Venture Capital backing dummy -0.762 -0.140 -12.33 -0.748 -0.286 -6.03 Use of proceeds dummy 0.343 0.136 3.54 Investment bank characteristics Carter-Manaster rank 0.009 0.008 0.60 0.016 0.014 0.55 Bank market share -0.031 -0.071 -4.38 -0.061 -0.140 -3.80 Bank industry market share -0.062 -0.358 -16.51 -0.049 -0.318 -6.75 Market conditions at time of filing Number of filings prior 2 months 0.002 0.038 2.88 0.002 0.027 0.94 Number of industry filings prior 2 months -0.007 -0.041 -1.64 -0.003 -0.017 -0.42 BAA-AAA yield spread at filing -1.133 -0.073 -6.38 -2.478 -0.030 -4.17 10-year Treasury yield at filing -0.002 -0.001 -0.05 -0.920 0.000 -7.94 Industry average book-to-market pre filing -0.490 -0.050 -3.33 -2.762 -0.128 -5.87 Market conditions after the filing Number of filings 2 months after filing -0.005 -0.066 -5.30 -0.005 -0.073 -2.71 Number of industry filings 2 months after filing -0.001 -0.004 -0.15 0.006 0.042 1.04 Change in BAA-AAA yield spread 2 month after filing -0.940 -0.036 -3.11 -2.648 -0.102 -3.98 Change in 10-year Treasury yield 2 months after filing -0.011 -0.002 -0.18 -0.273 -0.050 -1.76 Return on Nasdaq Composite Index 2 months after filing -2.043 -0.069 -6.59 -0.127 -0.004 -0.22 Change in industry BM over year of filing 0.909 0.035 2.31 0.200 0.008 0.20 Pseudo R2 0.243 0.380 Number of Observations 6284 5486

Table 4 Time from initial withdrawal to successful reissue for 138 IPOs from1985 to 2000 Length of time between withdrawn issue and successful re-issue. Probabilities indicate the chance of a successful re-issue based solely on length of time since withdrawn issue date.

Panel A

Day Years

Mean 818.6 2.24Median 657.5 1.8Minimum 77 0.21Maximum 3523 9.65Standard deviation 630.1 1.73

Panel B

Probability Days Years

95% 142 0.3990% 216 0.5985% 270 0.7480% 307 0.8475% 329 0.970% 378 1.0465% 427 1.1760% 517 1.4255% 604 1.6550% 663 1.8245% 777 2.1340% 828 2.2735% 928 2.5430% 963 2.6425% 1181 3.2420% 1291 3.5415% 1398 3.8310% 1628 4.465% 2223 6.09

Table 5 Descriptive Statistics – Withdrawn IPOs broken down by eventual public status This table reports sample means (mean) and number of observations (obs) for different variables broken down by whether the withdrawn filing eventually returns for a successful IPO or not. Issuer and issue characteristic variables are defined as follows. Average filing price is the average of the high and low price indicated in the initial filing. Filing size equals the average filing price multiplied by the number of shares to be sold as indicated in the initial filing (reported in January 2000 dollars using the CPI as a deflator). High-tech industry dummy takes the value 1 if the issuer is in Fama-French industries 34 (business services) or 36 (chips) and 0 otherwise (see Fama and French, 1997). Venture capital backing dummy takes the value 1 if the issuing firm has received venture capital investments prior to filing and 0 otherwise. Use of proceeds dummy takes the value 1 if the primary stated use of proceeds is retirement of debt. Debt to assets ratio is total debt pre filing divided by total assets pre filing. Investment bank characteristic variables are defined as follows. Carter-Manaster Rank is the Carter-Manaster (1990) ranking on a 0-9 scale for the book manager of the IPO (the maximum rank if there is more than one book manager). Bank market share is the sum of gross proceeds (not including the overallotment option) over the year prior to the IPO of all offe rings where the IPO book manager is the book manager (equal credit given if there is more than one manager) divided by the sum of gross proceeds on all IPOs over the same period. Bank industry market share is the sum of gross proceeds over the year prior to the IPO of all IPOs in the same Fama-French industry where the IPO book manager is the book manager divided by the sum of gross proceeds on all industry IPOs over the same period. Market condition variables at the time of the withdrawal are defined as follows: Number of filings prior 2 months is the number of IPOs filed with the SEC during the 2 months prior to the withdrawal date for the IPO. Number of industry filings prior 2 months is the number of IPOs in the same Fama -French industry filed with the SEC during the 2 months prior to the withdrawal date for the IPO. BAA-AAA yield spread at time of withdrawal is the spread between BAA and AAA corporate bonds (from Moody’s) on the day of the withdrawal. 10-year Treasury yield at withdrawal is the average yield on US Treasury bonds having 10 years to maturity measured on the day of the withdrawal. Industry average book-to-market pre withdrawal is the book to market ratio for firms in the IPO issuer’s Fama-French industry at the end of the year prior to withdrawal (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html). Change in industry BM over year pre withdrawal is the change in the IPO industry book-to-market ratio over the calendar year ending prior to the withdrawal. Return on Nasdaq Composite Index 2 months pre withdrawal is the compound return on the index over two months ending the withdrawal date. Market condition variables after the withdrawal are defined s follows. Number of filings 12 months after the withdrawal is the number of IPOs filed with the SEC during the 12 months after the withdrawal date for the IPO. Number of industry filings 12 months after the withdrawal is the number of IPOs in the same Fama -French industry filed with the SEC during the 12 months after the withdrawal date for the IPO. Change in BAA-AAA yield spread 12 months after withdrawal is the BAA-AAA yield spread12 months after the withdrawal date subtract the yield spread on the withdrawal date. Change in 10-year Treasury yield 12 months after withdrawal is the 10-year Treasury yield 12 months after the withdrawal date subtract the 10-year Treasury yield on the withdrawal date. Change in industry BM over year of withdrawal is the change in the IPO industry book-to-market ratio over the calendar year ending after the withdrawal. Return on Nasdaq Composite Index 12 months after withdrawal is the compound return on the index over 12 months beginning the withdrawal date.

Initial filing of withdrawn IPOs that

later return for successful offer

Initial filing of withdrawn IPOs that

never return for successful offer

p-values (from t-test) - not return

vs. return mean obs mean obs Issuer and issue characteristics Average filing price 14.133 120 15.270 956 0.507 Filing size 60.473 120 58.948 956 0.856 High-tech industry dummy 0.250 120 0.240 956 0.804 Venture Capital backing dummy 0.292 96 0.111 650 0.000 Use of proceeds dummy 0.281 32 0.445 274 0.064

Table 5, continued Descriptive Statistics – Withdrawn IPOs broken down by eventual public status

Initial filing of withdrawn IPOs that

later return for successful offer

Initial filing of withdrawn IPOs that

never return for successful offer

p-values (from t-test) - not return

vs. return mean obs mean obs Investment bank characteristics Carter-Manaster rank 7.445 120 6.522 956 0.000 Bank market share 2.055 120 1.860 956 0.633 Bank industry market share 1.160 120 2.911 956 0.000 Market conditions at time of withdrawal Number of filings prior 2 months 88.242 120 86.796 956 0.681 Number of industry filings prior 2 months 6.833 120 9.719 956 0.002 BAA-AAA yield spread at withdrawal 0.817 120 0.816 956 0.963 10-year Treasury yield at withdrawal 6.895 120 6.693 956 0.089 Industry average book-to-market pre withdrawal 0.445 120 0.423 956 0.416 Change in industry BM over year pre withdrawal -0.047 120 -0.033 956 0.421 Return on Nasdaq Composite Index from filing to withdrawal 0.023 120 0.033 956 0.491 Market conditions after the withdrawal Number of filings 12 months after withdrawal 501.390 120 452.760 956 0.002 Number of industry filings 12 months after withdrawal 39.000 120 39.171 956 0.974 Change in BAA-AAA yield spread 12 months after withdrawal -0.061 120 -0.003 956 0.000 Change in 10-year Treasury yield 12 months after withdrawal -0.126 120 -0.302 956 0.094 Change in industry BM over year of withdrawal -0.016 120 -0.004 956 0.057 Return on Nasdaq Composite Index 12 months after withdrawal 0.243 120 0.153 956 0.000

Table 6 Probit analysis of successful returns for IPO filings that were withdrawn between 1985 and 2000 The dependent variable equals one for IPO filings that are withdrawn but eventually return for a successful offering and zero for withdrawn offerings that never return. Issuer and issue characteristic independent variables are defined as follows. High-tech industry dummy takes the value 1 if the issuer is in Fama -French industries 34 (business services) or 36 (chips) and 0 otherwise (see Fama and French, 1997). Logarithm of filing size equals the natural logarithm of the product of the average filing price and the number of shares to be sold as indicated in the initial filing (reported in January 2000 dollars using the CPI as a deflator). Venture capital backing dummy takes the value 1 if the issuing firm has received venture capital investments prior to filing and 0 otherwise. Investment bank characteristic independent variables are defined as follows. Carter-Manaster Rank is the Carter-Manaster (1990) ranking on a 0-9 scale for the book manager of the IPO (the maximum rank if there is more than one book manager). Bank market share is the sum of gross proceeds (not including the overallotment option) over the year prior to the IPO of all offerings where the IPO book manager is the book manager (equal credit given if there is more than one manager) divided by the sum of gross proceeds on all IPOs over the same period. Bank industry market share is the sum of gross proceeds over the year prior to the IPO of all IPOs in the same Fama-French industry where the IPO book manager is the book manager divided by the sum of gross proceeds on all industry IPOs over the same period. Market condition independent variables at the time of the withdrawal are defined as follows: Number of filings prior 2 months is the number of IPOs filed with the SEC during the 2 months prior to the withdrawal date for the IPO. Number of industry filings prior 2 months is the number of IPOs in the same Fama-French industry filed with the SEC during the 2 months prior to the withdrawal date for the IPO. BAA-AAA yield spread at time of withdrawal is the spread between BAA and AAA corporate bonds (from Moody’s) on the day of the withdrawal. 10-year Treasury yield at withdrawal is the average yield on US Treasury bonds having 10 years to maturity measured on the day of the withdrawal. Industry average book-to-market pre withdrawal is the book to market ratio for firms in the IPO issuer’s Fama -French industry at the end of the year prior to withdrawal (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html). Return on Nasdaq Composite Index from filing to withdrawal is the compound return on the index from filing date to withdrawal date. Market condition independent variables after the withdrawal are defined s follows. Number of filings 12 months after the withdrawal is the number of IPOs filed with the SEC during the 12 months after the withdrawal date for the IPO. Number of industry filings 12 months after the withdrawal is the number of IPOs in the same Fama-French industry filed with the SEC during the 12 months after the withdrawal date for the IPO. Change in BAA-AAA yield spread 12 months after withdrawal is the BAA-AAA yield spread12 months after the withdrawal date subtract the yield spread on the withdrawal date. Change in 10-year Treasury yield 12 months after withdrawal is the 10-year Treasury yield 12 months after the withdrawal date subtract the 10-year Treasury yield on the withdrawal date. Change in industry BM over year of withdrawal is the change in the IPO industry book-to-market ratio over the calendar year ending after the withdrawal. Return on Nasdaq Composite Index 12 months after withdrawal is the compound return on the index over 12 months beginning the withdrawal date.Marginal effect is defined as φ(β�x)*β*σx where φ() is the standard normal probability density function, β is the coefficient estimate, x is the mean of the independent variable for the sample and σx is one standard deviation for the independent variable (σx is set to 1 for dummy variables). Pseudo R2 is defined as 1 subtract the log likelihood for the estimated model divided by the log-likelihood for a model with only an intercept as an independent variable.

Table 6, continued Probit analysis of successful returns for IPO filings that were withdrawn between 1985 and 2000

Coefficient Marginal

effect t-stat Coefficient Marginal

effect t-stat

Intercept -4.717 0.000 -5.58 -4.930 0.000 -3.43

Issuer and issue characteristics High-tech industry dummy 0.295 0.117 1.58 0.128 0.051 0.56 Logarithm of the filing size 0.028 0.014 0.40 -0.011 -0.005 -0.12 Venture Capital backing dummy 0.517 0.206 3.23 Investment bank characteristics Carter-Manaster rank 0.110 0.094 3.35 0.102 0.087 2.55 Bank market share 0.006 0.010 0.43 0.007 0.011 0.47 Bank industry market share -0.042 -0.138 -2.88 -0.052 -0.168 -2.53 Market conditions at time of withdrawal Number of filings 2 months prior to withdrawal 0.003 0.037 1.24 0.006 0.061 1.93 Number of industry filings 2 months prior to withdrawal -0.019 -0.105 -1.70 -0.026 -0.111 -1.73 BAA-AAA yield spread at withdrawal -0.901 -0.060 -1.88 0.023 0.001 0.03 10-year Treasury yield at withdrawal 0.399 0.005 4.41 0.393 0.006 2.54 Industry average book-to-market pre withdrawal -0.343 -0.032 -1.24 -0.700 -0.050 -1.58 Return on Nasdaq Composite Index from filing to withdrawal -1.228 -0.093 -2.80 -1.395 -0.080 -2.45 Market conditions after the withdrawal Number of filings 12 months after withdrawal 0.001 0.079 2.11 0.001 0.031 1.01 Number of industry filings 12 months after withdrawal 0.002 0.047 0.93 0.003 0.075 1.16 Change in BAA-AAA yield spread 12 month after withdrawal -0.654 -0.051 -1.28 0.047 0.003 0.06 Change in 10-year Treasury yield 12 months after withdrawal 0.287 0.119 3.71 0.291 0.124 2.59 Change in industry BM over year of withdrawal -1.003 -0.032 -1.14 -1.571 -0.039 -1.30 Return on Nasdaq Composite Index 12 months after withdrawal 0.326 0.040 1.15 0.105 0.011 0.30 Pseudo R2 0.124 0.125 Number of Observations 1076 746

Table 7 Tests of the graduation hypothesis This table presents descriptive statistics on variables for a subsample of IPOs that are withdrawn and later return for a successful or failed IPO using a different investment bank from the first attempt. Variables examined are defined as follows. IPO market share is the sum of gross proceeds (not including the overallotment option) over the year prior to the IPO of all offerings where the IPO book manager is the book manager (equal credit given if there is more than one manager) divided by the sum of gross proceeds on all IPOs over the same period. Market share is defined as of the date of the filing leading up to the second attempt. IPO industry market share is defined similarly to overall IPO market share where only issues in the IPO firm’s Fama-French industry (see Fama-French 1997) are considered. IPO industry market share is defined as of the date of the filing leading up to the second attempt. Carter-Manaster Rank is the Carter-Manaster (1990) ranking on a 0-9 scale for the book manager of the IPO (the maximum rank if there is more than one book manager).

initial bank on first failed filing (at time of second

attempt)

new bank on subsequent

successful filing change

t-statistic (H0: initial bank = second bank)

Panel A - All withdrawn IPOs that subsequently return for a successful offer with a different bank (98 observations)

IPO market share Mean 3.608 4.863 1.254 1.57 Median 0.846 2.823 0.901 IPO industry market share Mean 2.327 15.690 13.363 5.82 Median 0.000 7.212 5.528 Carter Manaster Ranking Mean 7.288 7.575 0.287 1.31 Median 8.100 8.100 0.000

Panel B - All withdrawn IPOs that subsequently return for an unsuccessful offer with a different bank (15 observations)

IPO market share Mean 1.024 2.641 1.617 2.02 Median 0.141 1.269 0.536 IPO industry market share Mean 3.649 1.552 -2.097 -1.00 Median 0.325 0.000 0.000 Carter Manaster Ranking Mean 7.963 6.833 -1.130 -1.90 Median 8.100 7.100 -1.000

Table 8 Tests of the IPO performance hypothesis This table presents descriptive statistics on variables for a subsample of IPOs that are withdrawn and later return for a second attempt. Sub samples are examined based on whether the issuer changes investment banks from the first failed attempt to the eventual successful offering. The variables examined are defined as follows. IPO filing size –initial unsuccessful filing equals the average filing price (average of the high and low price indicated in the initial filing) multiplied by the number of shares to be sold as indicated in the initial (unsuccessful) filing. IPO filing size –second attempt equals the average filing price (average of the high and low price indicated in the initial filing) multiplied by the number of shares to be sold as indicated in the initial filing for the second IPO attempt. Abnormal filing size is defined as the filing size subtract the average filing size in IPOs over the 6 months leading up to the fling. Abnormal percent change in filing size is defined as the abnormal filing size in the second attempt divided by the abnormal filing size in the initial attempt, subtract one. All dollar amounts are converted to January 2000 dollars using the CPI.

All withdrawn IPOs that

subsequently return for a successful

offer

All withdrawn IPOs that

subsequently return for an unsuccessful

offer

t-statistic (H0:

successful returners = non-

successful returners)

Successful returning IPOs

where the investment bank is

switched from initial unsuccessful

filing

Successful returning

IPOs where the

investment bank is not switched

t-statistic (H0:

switchers = non-

switchers) Mean IPO filing size - initial unsuccessful filing 51.013 28.413 3.16 43.773 73.479 1.77 Mean IPO filing size – second attempt 64.719 34.360 3.32 65.622 61.914 -0.25 Mean Percent change in filing size 107.184 31.780 1.42 139.730 6.180 -1.97 t -statistic (H0: percent change = 0) 2.10 2.17 2.08 0.66 Mean Abnormal percent change in filing size 72.202 9.575 1.18 103.116 -23.737 -1.84 t -statistic (H0: percent change = 0) 1.40 0.77 1.52 -2.06 Number of observations 119 15 90 29

Table 9 Interactions between the graduation and performance hypotheses This table presents descriptiv e statistics on variables for subsamples of IPOs that are withdrawn and later return for a second successful attempt using a different investment bank. The independent variables examined are defined as follows. Mean percentage change in IPO filing size is the IPO filing size (average of the high and low price indicated in the initial filing multiplied by the number of shares to be sold as indicated in the initial filing) for the second successful filing divided by the IPO filing size on the first unsuccessful attempt, subtract one. Abnormal filing size is defined as the filing size subtract the average filing size in IPOs over the 6 months leading up to the fling. Abnormal percent change in IPO filing size is defined as the abnormal filing size in the second attempt divided by the abnormal filing size in the initial attempt, subtract one. All dollar amounts are converted to January 2000 dollars using the CPI.. Subsamples are examined based changes in investment bank reputation measures upon change in underwriter. Reputation measures are defined as follows. IPO market share is the sum of gross proceeds (not including the overallotment option) over the year prior to the IPO of all offerings where the IPO book manager is the book manager (equal credit given if there is more than one manager) divided by the sum of gross proceeds on all IPOs over the same period. Market share is defined as of the date of the filing leading up to the second attempt. IPO industry market share is defined similarly to overall IPO market share where only issues in the IPO firm’s Fama-French industry (see Fama-French 1997) are considered. IPO industry market share is defined as of the date of the filing leading up to the second attempt. Carter-Manaster Rank is the Carter-Manaster (1990) ranking on a 0-9 scale for the book manager of the IPO (the maximum rank if there is more than one book manager).

Mean Percentage Change in IPO filing

size

t-statistic (H0: change

in filing size = 0)

Number of observations

Mean abnormal

percentage change in IPO filing

size

t-statistic (H0:

change in filing size

= 0)

Number of observations

IPO market share increases with bank change 181.376 1.91 63 136.503 1.42 63

IPO market share does not increase with bank change 42.557 1.49 27 25.215 0.93 27 t -statistic (H0: group with market share increase = group with market share decrease) 1.40 1.11

IPO industry market share increases mo re than 2% with change 172.992 2.14 71 131.572 1.74 71 IPO industry market share increases less than or equal to 2% with change 15.434 1.20 19 -3.217 -0.20 19

t -statistic (H0: group with large industry market share increase = group with smaller industry market share increase)

2.04 1.90

Bank Carter-Manaster ranking increases with bank change 242.784 1.72 42 186.828 1.30 42

Bank Carter-Manaster ranking does not increase with change 49.558 2.52 48 29.868 1.58 48

t -statistic (H0: group with market share increase = group with market share decrease) 1.35 1.08

Table 10 The probability of return, bank switching and the choice to withdraw an IPO for filings between 1985 and 2000 The dependent variable equals one for IPO filings that are withdrawn and zero for completed offerings. Independent variables are defined as follows. Issuer and issue characteristic independent variables are defined as follows. High-tech industry dummy takes the value 1 if the issuer is in Fama-French industries 34 (business services) or 36 (chips) and 0 otherwise (see Fama and French, 1997). Logarithm of the filing size equals the natural logarithm of the average filing price multiplied by the number of shares to be sold as indicated in the initial filing (reported in January 2000 dollars using the CPI as a deflator). Venture capital backing dummy takes the value 1 if the issuing firm has received venture capital investments prior to filing and 0 otherwise. Investment bank characteristic independent variables are defined as follows. Carter-Manaster Rank is the Carter-Manaster (1990) ranking on a 0-9 scale for the book manager of the IPO (the maximum rank if there is more than one book manager). Bank market share is the sum of gross proceeds (not including the overallotment option) over the year prior to the IPO of all offerings where the IPO book manager is the book manager (equal credit given if there is more than one manager) divided by the sum of gross proceeds on all IPOs over the same period. Bank industry market share is the sum of gross proceeds over the year prior to the IPO of all IPOs in the same Fama-French industry where the IPO book manager is the book manager divided by the sum of gross proceeds on all industry IPOs over the same period. Market condition independent variables at the time of the issue / withdrawal are defined as follows. Number of filings prior 2 months is the number of IPOs filed with the SEC during the 2 months prior to the issue/ withdrawal date for the IPO. Number of industry filings prior 2 months is the number of IPOs in the same Fama-French industry filed with the SEC during the 2 months prior to the issue/ withdrawal date for the IPO. BAA-AAA yield spread at time of issue/withdrawal is the spread between BAA and AAA corporate bonds (from Moody’s) on the day of the withdrawal. 10-year Treasury yield at withdrawal is the average yield on US Treasury bonds having 10 years to maturity measured on the day of the issue / withdrawal. Return on Nasdaq Composite Index from filing to issue / withdrawal is the compound return on the index from filing date to withdrawal date. Industry average book-to-market pre issue/ withdrawal is the book to market ratio for firms in the IPO issuer’s Fama-French industry at the end of the year prior to issue / withdrawal (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html). Firm and bank characteristic variables at issue / withdrawal are defined as following. Probability of successful return if withdrawn is estimated using a probit model estimated using a sample of withdrawn IPOs. Independent variables in the model include Issuer and issue characteristics, investment bank characteristics and market conditions at time of withdrawal variables defined in table 6 (no variables are included that are measured after withdrawal). The probit model estimates are then used to generate predicted probability of return for all IPO filings (measured at time of issue / withdrawal). Investment bank change dummy equals one if the offering is a second attempt and the bank used on the second attempt is different than used on the first attempt. Change in bank industry market share if bank is changed is equal to the difference between the industry market share of the banks on the second and first attempts in cases where the bank has changed and the offering is a second attempt. Marginal effect is defined as φ(β�x)*β*σx where φ() is the standard normal probability density function, β is the coefficient estimate, x is the mean of the independent variable for the sample and σx is one standard deviation for the independent variable (σx is set to 1 for dummy variables). Pseudo R2 is defined as 1 subtract the log likelihood for the estimated model divided by the log-likelihood for a model with only an intercept as an independent variable.

Table 10, continued The probability of return, bank switching and the choice to withdraw an IPO for filings between 1985 and 2000 All IPO filers Second time filers

Coefficient Marginal

effect t-stat Coefficient Marginal

effect t-stat

Intercept 0.257 0.099 1.04 1.661 0.167 0.97 Issuer and issue characteristics High-tech industry dummy -0.284 -0.113 -3.54 -2.586 -0.835 -1.95 Logarithm of the filing size 0.333 0.072 9.15 -0.251 -0.060 -0.57 Venture Capital backing dummy -0.892 -0.338 -12.82 -0.711 -0.265 -1.10 Investment bank characteristics Carter-Manaster rank -0.003 -0.002 -0.17 Bank market share -0.039 -0.089 -5.59 Bank industry market share -0.059 -0.352 -15.37 -0.102 -0.009 -1.47 Market conditions at the time of issue / withdrawal Number of filings prior 2 months -0.006 -0.067 -6.92 -0.022 -0.001 -1.79 Number of industry filings prior 2 months -0.012 -0.063 -3.84 0.001 0.001 0.02 BAA-AAA yield spread at issue / withdrawal -0.915 -0.068 -5.93 10-year Treasury yield at issue / withdrawal -0.023 -0.011 -0.80 Return on Nasdaq Composite Index from filing to issue/withdrawal -0.879 -0.084 -5.77 -1.369 -0.545 -0.56 Industry average book-to-market pre issue / withdrawal 1.029 0.048 5.43 Firm and bank characteristics at issue /withdrawal Probability of successful return if withdrawn 0.927 0.071 4.85 1.251 0.490 0.65 Investment bank change dummy 2.895 0.106 3.20 Change in bank industry market share if bank is changed -2.795 -0.281 -3.21

Pseudo R2 0.249 0.704 Number of Observations 6284 143

Table 11 Price adjustments and Initial returns for IPOs between 1985 and 2000 The dependent variables are defined as follows. Price Adjustment is the IPO offer price divided by the average of the high and low initial filing price. Initial return defined as 100*(P1-P0)/P0 where P1 is the first-day closing stock price or bid-ask average (from CRSP) and P0 is the IPO offer price. Independent control variables are defined as follows. Price Revision is the IPO offer price divided by the average of the high and low initial filing price. Price Revision + is the IPO offer price divided by the average of the high and low initial filing price if positive and zero otherwise. Overhang is (S1-S)/S where S1 is the shares outstanding after the IPO and S is the shares offered in the IPO. Venture Capital Backing equals 1 if the issue is venture capital-backed and 0 otherwise. AMEX equals 1 if the IPO lists on the American Stock Exchange and 0 otherwise. Firm Std. Deviation equals the standard deviation of daily stock returns for the issuing firm from days 21 to 50 relative to the IPO. Market Return equals the buy and hold CRSP value-weighted index return from days -50 to -2 relative to the IPO. Market Return + equals the buy and hold CRSP value-weighted index return from days -50 to -2 relative to the IPO if positive, 0 otherwise. Market Std. Deviation is the standard deviation of daily returns for the CRSP value-weighted index from days -50 to -2 re lative to the IPO. Lagged Avg. Underpricing is the average initial return for issues on days -60 to -1 relative to the IPO. Number of Prior IPOs is the number of issues from days -60 to -1 relative to the IPO. Number of Prior industry IPOs is the number of issues in the same Fama-French industry over the year prior to the IPO. Carter-Manaster Rank is the Carter-Manaster (1990) ranking on a 0-9 scale for the book manager of the IPO (the maximum rank if there is more than one book manager). Independent variables indicating effects of withdrawals are defined as follows. Dummy – high withdrawal and low return likelihood (HW-LR) is a dummy variable generated using predictions from ex ante probit models of withdrawal and returning. . Probability of successful return if withdrawn is estimated using a probit model estimated using a sample of withdrawn IPOs. Independent variables in the model include Issuer and issue characteristics, investment bank characteristics and market conditions at time of withdrawal variables defined in Table 6 (no variables are included that are measured after withdrawal). The probit model estimates are then used to generate predicted probability of return for all IPO filings (measured at time of issue / withdrawal). Probability of withdrawal is estimated using a probit model of all IPO filings. Independent variables in the model include Issuer and issue characteristics, investment bank characteristics and market conditions at time of issue withdrawal variables defined in Table 6 and 10 (no variables are included that are measured after issue withdrawal). The probit model estimates are then used to generate predicted probability of withdrawal for all IPO filings (measured at time of issue / withdrawal). The dummy variable in this regression equals one if the probability of withdrawal exceeds 2% and the probability of return is less than 13% (mean values for the variables). HW-LR * price revision and HW-LR * price revision + are interactive variables. Independent variables indicating whether IPO was previously withdrawn are defined as follows. Previously withdrawn IPO dummy takes the value 1 if the IPO was from a firm that previously attempted and withdrew their offering. Previously withdrawn IPO with change in bank takes the value 1 if the IPO was from a firm that previously attempted and withdrew their offering and are using a different investment bank on their successful offering. Previously withdrawn IPO with no change in bank takes the value 1 if the IPO was from a firm that previously attempted and withdrew their offering and are using the same investment bank on their successful offering.

Table 11, continued Price adjustments and Initial returns for IPOs between 1985 and 2000 Price Adjustment Price Adjustment Initial Return Initial Return Coefficient t-stat Coefficient t-stat Coefficient t-stat Coefficient t-stat Control Variables Intercept -0.115 -7.65 -0.115 -7.66 -3.973 -1.67 -4.030 -1.70 Price Revision 23.101 4.83 23.141 4.84 Price Revision + 109.024 16.59 108.970 16.59 Overhang 0.015 11.29 0.015 11.26 1.978 9.65 1.972 9.62 Venture Capital Backing 0.014 2.13 0.014 2.16 -0.603 -0.60 -0.548 -0.54 NYSE 0.018 1.80 0.017 1.75 -2.903 -1.92 -3.009 -1.99 AMEX -0.068 -4.39 -0.068 -4.38 -4.856 -2.03 -4.830 -2.02 Firm Std. Deviation 0.015 10.18 0.015 10.18 2.286 9.61 2.292 9.64 Market Return 0.012 6.13 0.012 6.11 -0.421 -1.39 -0.430 -1.42 Market Return + -0.006 -2.44 -0.006 -2.42 0.559 1.56 0.567 1.58 Market Std. Deviation 0.004 0.35 0.004 0.33 3.717 2.13 3.710 2.13 Lagged Avg. Underpricing 0.361 12.77 0.359 12.68 Number of Prior IPOs -0.001 -6.29 -0.001 -6.24 -0.024 -1.65 -0.023 -1.57 Number of Prior Industry IPOs 0.001 8.54 0.001 8.55 -0.004 -0.47 -0.004 -0.43 Carter-Manaster Rank 0.004 2.91 0.004 2.90 -0.932 -4.57 -0.933 -4.58 Variables indicating effects of withdrawals Dummy -high withdrawal and low return likelihood (HW-LR) -0.017 -2.10 -0.017 -2.08 0.327 0.20 0.337 0.21 HW-LR * Price Revision 14.464 1.37 13.775 1.31 HW-LR * Price Revision + -96.676 -6.91 -96.000 -6.86 Variables indicating whether IPO was previously withdrawn Previously withdrawn IPO dummy -0.025 -1.35 2.744 0.95 Previously withdrawn IPO with no change in bank 0.017 0.47 -1.221 -0.37 Previously withdrawn IPO with change in bank -0.040 -1.85 13.823 2.49

Adjusted R2 0.132 0.132 0.464 0.464 Number of Observations 5564 5564 5564 5564