Where ahve all ip os gone?

Electronic copy available at: http://ssrn.com/abstract=1954788
Where Have All the IPOs Gone?
Xiaohui Gaoa
, Jay R. Ritterb,*
, Zhongyan Zhuc
August 26, 2013
Key Words: IPO volume; trade sales; economies of scope; effects of Sarbanes-Oxley; VC exits
JEL Codes: G24, G38
a
University of Maryland and University of Hong Kong, b
University of Florida, c
Chinese
University of Hong Kong
*
Corresponding author: jay.ritter@warrington.ufl.edu
Comments from Dan Bradley, Harry DeAngelo, Jarrad Harford (the editor), Jerry Hoberg,
Po-Hsuan Hsu, Peter Iliev, Andrew Karolyi, Leming Lin, Tim Loughran, René Stulz, David
Weild, and participants in the 2011 Kauffman Entrepreneurship and 2012 China International
Conference in Finance conferences and seminars at the Chinese University of Hong Kong,
Harvard, Louisiana State University, Ohio State, Renmin, and the Universities of Cambridge,
Hong Kong, Iowa, Kansas, Missouri, South Florida, and Warwick are appreciated.
Comments from Gurdip Bakshi are especially appreciated.

Electronic copy available at: http://ssrn.com/abstract=1954788
1
Abstract
During 1980-2000, an average of 310 companies per year went public in the U.S. Since 2000, the
average has been only 99 initial public offerings (IPOs) per year, with the drop especially
precipitous among small firms. Many have blamed the Sarbanes-Oxley Act of 2002 and the 2003
Global Settlement’s effects on analyst coverage for the decline in IPO activity. We find very little
support for the conventional wisdom, and offer an alternative explanation. Our economies of
scope hypothesis posits that the advantages of selling out to a larger organization, which can
speed a product to market and realize economies of scope, have increased relative to the benefits
of operating as an independent firm.

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1. Introduction
The number of initial public offerings (IPOs) in the U.S. dropped from an average of 310
IPOs per year during 1980-2000 to only 99 IPOs per year during 2001-2012. The low level of
IPOs this decade has generated much discussion among private company executives, stock
exchange officials, policy-makers, and the financial press, as well as among venture capitalists
and buyout firms that depend on an active IPO market for exits. Commentators have expressed
concern that the lack of a vibrant IPO market could limit Gross Domestic Product (GDP) and
employment growth (e.g., Weild and Kim (2009)). In an attempt to generate more IPOs, the
Jumpstart Our Business Startups (JOBS) Act was signed into law in April 2012.
Two main explanations for the prolonged drought in IPOs have been advanced. First, the
Sarbanes-Oxley Act of 2002 (SOX), particularly Section 404, imposed additional compliance
costs on publicly traded firms. As a percentage of revenue, these costs have been especially
onerous for small firms. Consistent with the SOX explanation for the decline in IPO activity, the
decline in IPOs has been most pronounced among small firms.
Second, others have attributed the drop in small company IPO volume to a decline in the
“ecosystem” of underwriters that focus on smaller firms and provide analyst coverage after a
company has gone public. Explanations for why the ecosystem has declined have focused on the
drop in bid-ask spreads that began in 1994 and the effect of this drop on the incentives for
analysts to cover small firms. The U.S. Securities and Exchange Commission’s (SEC)
Regulation FD (Fair Disclosure) in 2000 and the 2003 Global Settlement have also been blamed

3
(see Zweig (2010) and Weild (2011)).1
This analyst coverage explanation assumes that small
company valuation ratios (e.g., price-to-earnings and market-to-book ratios) are higher if there is
more analyst coverage, decreasing the cost of equity capital from public markets. Consistent with
the lack of analyst coverage explanation, Jegadeesh and Kim (2010, Table 1) report that both the
number of firms covered and the number of sell-side analysts peaked in 2002 and then declined.
We term the above explanations the regulatory overreach hypothesis. All of the above
explanations for the low volume of IPOs since 2000 can be summarized with the phrase “the IPO
market is broken.” Although we do not argue that nothing is wrong with the IPO market, our
explanation for the dearth of IPOs since 2000 is fundamentally different.
In this paper, we introduce a new explanation for the prolonged low level of U.S. IPO
volume, which we term the economies of scope hypothesis. We posit that there is an on-going
change in the economy that has reduced the profitability of small companies, whether public or
private. We contend that many small firms can create greater operating profits by selling out in a
trade sale (being acquired by a firm in the same or a related industry) rather than operating as an
independent firm and relying on organic (i.e., internal) growth. Earnings will be higher as part of
a larger organization that can realize economies of scope and bring new technology to market
faster.2
We posit that the importance of getting big fast has increased over time due to an
increase in the speed of technological innovation in many industries, with profitable growth
opportunities potentially lost if they are not quickly seized.
Both the regulatory overreach and the economies of scope hypotheses attribute the drop in
1
In a 2009 survey, SOX, Corporate Governance, and Reg FD were listed as among the top three compliance
challenges for small companies thinking of going public. This survey was conducted by venture capital firm DCM
and the results were included in the March 2011 presentation of National Venture Capital Association Chair Kate
Mitchell at the U.S. Treasury’s Access to Capital conference.
2
Economies of scope exist when the average cost of production, including marketing and distribution costs, are
lower when related products are produced as part of a larger organization than when produced by independent
organizations. For example, a pharmaceutical company that sells two types of antibiotics is likely to have lower
costs per unit than if two independent companies each sell one antibiotic.

4
the number of small company IPOs to low public market prices relative to their valuations in a
trade sale. The conventional wisdom, however, states that low public market prices are due to
either lower valuations caused by the lack of analyst coverage, or to lower earnings as a public
firm because of SOX and other costs. In contrast, our explanation for why many small firms are
choosing not to remain independent, but instead merging as a way of getting big fast, is that
earnings before compliance costs are higher as part of a larger organization that can realize
economies of scope and economies of scale.
We present numerous facts that are consistent with our economies of scope hypothesis and
inconsistent with the regulatory overreach hypothesis as an explanation for this prolonged drop
in IPO activity. We report that among small firms, the percentage of IPOs from the prior three
year that are unprofitable was below 60% in every year from 1980-1997, and has been above
60% in every year since then. In contrast, for large company IPOs the percentage reporting
negative post-IPO earnings has shown only a small increase, other than a temporary jump after
the 1999-2000 internet bubble. We also analyze the profitability of small and large
Compustat-listed companies that have been public for more than three years, and construct a
“what-if” measure of profitability by excluding SOX-related costs from expenses. We find that
the pattern of low profitability for small firms persists. Importantly, the downtrend in the
profitability of small companies started far before the regulatory changes that began with the
SOX Act of 2002.
Of the firms that do go public, the fraction of issuers that are acquired or make acquisitions
within a few years of going public has increased over time. Increasingly, recent IPOs do not rely
exclusively on organic growth to expand. Of those that are acquired, we show that most are
acquired by other publicly traded companies, and that there has been no increase in the fraction
of acquisitions by private companies or buyout firms. In other words, recent IPOs that

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voluntarily delist are not going private as a stand-alone company in an attempt to avoid SOX
costs, nor do they delist because of insufficient analyst coverage. Importantly, the increased
frequency of mergers began long before public market valuations declined starting in 2000.
Following concerns that the implementation of SOX, especially Section 404, was imposing
excessive costs on small public companies, in June 2007 the SEC revised some of the rules,
lessening the burdens on small companies.3
Inconsistent with the regulatory overreach
hypothesis, the number of small company IPOs has not increased since then.
Furthermore, relatively few U.S. firms have chosen to go public abroad (Caglio, Hanley,
and Marietta-Westberg (2012, Table III)), and foreign listings have not been disproportionately
affected (Doidge, Karolyi, and Stulz (2009, Table 7)). We report that the percentage of U.S. IPOs
that are from foreign firms has been higher in every year since 2004 than in all but a handful of
prior years. In many other developed countries, including Germany and France, IPO volume has
also been low since 2000.4
Of companies that do go public in the U.S., we report that there has been no drop in analyst
coverage. We also document that for the last three decades the long-run returns earned by
investors on small company IPOs have been poor, with the relative performance of small
company IPOs particularly disappointing after 2000. Vismara, Paleari, and Ritter (2012, Table 5)
report similar patterns for Europe. Taken together, these patterns suggest that while SOX and the
combined effects of decimalization and the Global Settlement on analyst coverage may have had
3
The U.S. SEC released its interpretive guidance on June 27, 2007, and the Public Company Accounting Oversight
Board approved Auditing Standard No. 5 for public accounting firms on July 25, 2007. On September 15, 2010, the
SEC issued final rule 33-9142, which permanently exempts registrants that are neither accelerated nor large
accelerated filers from the Section 404(b) internal controls audit requirement.
4
Vismara, Paleari, and Ritter (2012, Table 2) report that an average of 79 IPOs per year occurred on the main
markets of London, Paris, Milan, and Frankfurt combined during 1995-2000. During 2001-2009, this aggregate
annual average for the four largest economies in Europe fell to 41 IPOs per year, in spite of the inclusion of IPOs
starting in January 2005 from Belgium, the Netherlands, and Portugal after the Paris Bourse merged with these
markets to create Euronext.

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some effect on small company IPOs in the U.S., the more fundamental problems are the absence
of profitable small companies and the paucity of small companies that grow and become highly
profitable, earning high returns for investors.
Our hypothesis that economies of scope and speeding products to market have become
more important over time suggests a gradual decrease in the number of small company IPOs,
rather than the abrupt and, to date, permanent decline that occurred when the tech stock bubble
collapsed after March of 2000. To control for other determinants of IPO volume, we test the
leading explanations for the decline in IPO volume in a time-series regression framework with
the quarterly volume of IPOs scaled by real GDP as the dependent variable. Explanatory
variables include a time trend, reflecting the increasing importance of economies of scope, and a
dummy variable for the post-SOX era, while controlling for business conditions, the profitability
of small firms, the market-to-book ratio of small firms, and lagged and future returns on the
Nasdaq index. Our economies of scope hypothesis predicts a negative coefficient on the time
trend variable, whereas the regulatory overreach hypothesis predicts a negative coefficient on the
SOX dummy variable.
In our regressions, we obtain a negative and statistically significant coefficient for the time
trend, supporting our economies of scope hypothesis. Furthermore, there is a stronger downtrend
for small firm IPOs than for large firm IPOs. In contrast, the coefficient on the SOX dummy
variable is close to zero and statistically insignificant in all of our specifications. Our results also
show that market conditions can explain only some of the low IPO volume after 2000. IPO
volume has been below what would have been expected, given the usual response of IPO volume
to public market valuations, since 1997.
Perhaps the closest related work focusing on economies of scope as an explanation of IPO
activity is by Bayar and Chemmanur (2011), who model the choice of going public as a tradeoff

7
between an entrepreneur retaining the private benefits of control by staying private versus
realizing higher wealth due to economies of scale and scope from the IPO proceeds. Our analysis
goes a step further, positing that by selling out rather than going public, the firm is able to
achieve even greater economies of scale and scope. Because we are interested in explaining the
time series rather than the cross section of IPO activity, we do not focus on private benefits of
control, since we are not aware of any reason to think that they have materially changed over
time.
To the best of our knowledge, our economies of scope hypothesis offers a completely new
explanation for the drop in U.S. IPO activity after 2000. Although our evidence supporting the
hypothesis is largely indirect, our hypothesis is consistent with several patterns for which there
has been no consistent explanation: a decline in small firm profitability starting in the early
1990s, an increase in the probability of being involved in M&A activity beginning in the
mid-1990s, a decrease in the probability of a VC-backed company exiting via an IPO starting in
the early 1990s, and a lower number of IPOs relative to what would be predicted on the basis of
public market valuation ratios starting in 1997. Furthermore, we are unaware of any patterns that
are inconsistent with our explanation. If our economies of scope explanation is correct,
regulatory reforms aimed at restoring the IPO ecosystem will have only a modest ability to affect
IPO volume, and a bull market will not set off a wave of small company IPOs.
2. The Decline in U.S. IPO Activity
Table 1 and Figure 1 show the number of companies going public in the U.S. by year during
1980-2012. Some of our analysis covers IPOs from this 33 year period, although we end with
IPOs from 2009 or 2011 when we focus on post-IPO behavior or, due to the availability of data,
start with a different year than 1980. Throughout, we restrict our definition of IPOs to exclude

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non-operating companies, thus excluding closed-end funds, REITs, and special purpose
acquisition companies (SPACs). Furthermore, we screen out IPOs with an offer price lower than
$5 per share, unit offers, small best efforts offers, bank and S&L IPOs, limited partnerships, and
companies not listed on CRSP within six months of the IPO date. Finally, we screen out foreign
company IPOs that use American Depositary Receipts (ADRs), except in Table 4 when we show
that the percentage of IPOs from foreign issuers has increased over time.
Table 1 and Figure 1 show that the number of IPOs each year after 2000 has been low by
the standards of the 1980s and 1990s. The average annual volume of operating company IPOs
fell from 310 during 1980-2000 to only 99 during 2001-2012. The low volume of IPOs in the last
decade is even more noteworthy considering that real GDP more than doubled during our sample
period. The decline in IPO activity has been particularly noteworthy for small firms (those with
pre-issue annual sales of less than $50 million, expressed in 2009 purchasing power), with
average small company volume declining from 165 IPOs per year in 1980-2000 to 28 IPOs per
year in 2001-2012.5
The market has also witnessed a decline in large company IPOs, from an
annual average of 145 IPOs in 1980-2000 to 71 IPOs in 2001-2012. The average annual IPO
volume during 2001-2012 is significantly lower than the 1980-2000 average at the 1% level, as is
the drop in small company volume relative to the drop in large company volume. At the same
time, when annual volume is measured using total gross proceeds (expressed in 2009 purchasing
power, as shown in the right-most column of Table 1), neither a discrete drop after 2000 nor a
time trend are apparent.
We focus on this low-frequency change in the volume of IPOs, especially the volume of
5
Pre-IPO sales and earnings per share (EPS) numbers come from the Thomson Reuters new issues database, but we
make hundreds of corrections and inclusions of missing data items. The main sources of the additional information
are the U.S. SEC’s online EDGAR database (Prospectuses are SEC Form 424 filings) for IPOs after mid-1996, and
the Graeme Howard/Todd Huxster collection of IPO prospectuses for 1975-1996, and Dealogic for 1990-2012. The
Graeme Howard/Todd Huxster set of prospectuses is also used for post-1996 foreign firms, since in the late 1990s
Form F-1 prospectus filings were not filed electronically.

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small company IPOs, that is the focus of practitioner and policymaker concern. Other articles
attempt to explain the variations in monthly, quarterly, or yearly volume, such as Lerner (1994),
Lowry and Schwert (2002), Lowry (2003), Helwege and Liang (2004), Benninga, Helmantel,
and Sarig (2005), Pástor and Veronesi (2005), Yung, Çolak, and Wang (2008), and Rau and
Stouraitis (2011). We now proceed to document a number of patterns consistent with our
economies of scope hypothesis.
3. The Profitability of Small and Large Firms
3.1 The profitability of publicly traded small and large firms over time
In Table 2, we report the percentage of publicly traded firms with negative EPS each year
from 1980-2011.6
We report this percentage for small and large company IPOs (columns 2 and 4)
from the prior three years, and small and large seasoned firms (columns 6 and 8), which we
define as firms that have been CRSP-listed for at least three years. We define small and large IPO
firms using a cutoff of $50 million (2009 purchasing power) in pre-IPO last twelve month (LTM)
sales. For seasoned firms, we define small and large firms using a cutoff of $250 million (2009
purchasing power) in annual sales. Our rationale for using different cutoffs for recent IPOs and
for seasoned firms is that most IPOs are rapidly growing at the time of the IPO, and many
companies that had less than $50 million in sales in the year before going public grow in the
years after the IPO to exceed this threshold. Restricting the definition of seasoned firms to a $50
million annual sales cutoff would result in a relatively tiny sample of small seasoned firms, with
biotech firms and seasoned “loser” firms overrepresented. Our qualitative conclusions, however,
are not sensitive to the exact cutoffs.
6
We end in 2011 because the Compustat-reported earnings numbers for 2012 were not available when we did our
analysis. Compustat variable EPSPX: Basic Earnings Per Share Excluding Extraordinary Items is used to classify a
firm’s fiscal year as reporting nonnegative or negative EPS.

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Column 2 of Table 2 shows a dramatic increase in the percentage of recent small company
IPOs reporting losses over time. In every fiscal year from 1980-1991, less than 50% of small
company IPOs from the previous three years were unprofitable. By contrast, in every single year
since then, more than 50% of small company IPOs from the prior three years have been
unprofitable. For large company IPOs, column 4 shows an increase, too, although the percentage
reporting a loss never rises as high. In Appendix Table A-1, we report that the Table 2 patterns
are stronger in the technology sector than the non-tech sector.
For firms that have been publicly traded for at least three years, column 6 (small firms) and
column 8 (large firms) of Table 2 show the same patterns as for the recent IPOs, although the
increases in the percentage of firms reporting losses are not as extreme. In addition to the trends,
business cycle effects are also present, especially for the large seasoned firms.
Our findings are in line with those reported by Fama and French (2004, Table 4 and Figure
3), who also report a corresponding increase in the fraction of both public firms and recent IPOs
that are unprofitable during their 1973-2001 sample period. Likewise, DeAngelo, DeAngelo, and
Skinner (2004, Table 6) document that the biggest firms generate a much higher proportion of
aggregate earnings in 2000 than in 1978. They emphasize that the largest firms have been
gaining a higher fraction of aggregate profits, consistent with our explanation for why fewer
small private firms are choosing to remain independent by going public, rather than selling out in
a trade sale.
Why has small firm profitability declined? Our contention is that the advantage of being a
large firm has increased over time due to changes in technology and globalization, the same
forces responsible for the increase in the right-skewness of the distribution of income and wealth
at the personal level.7
Getting big fast has become more important in many industries because
7
A non-technical discussion of the causes with some academic references is contained in the Economist magazine’s

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the speed of technological change has increased.8
Two pieces of evidence support this contention. First, both Sorescu, Chandy, and Prabhu
(2003, Table 5) and Sood and Tellis (2005, p. 161) document that in recent years, most new
technologies have been introduced by large firms. Second, Sood and Tellis suggest that the pace
of technological change has increased over time, placing small firms at a disadvantage because
they lack the resources to quickly take advantage of new technologies.
Another related explanation for the decline in small firm profitability after 1995 is that the
internet has made comparison shopping easier for consumers, as argued by Goldmanis, Hortacsu,
Syverson, and Emre (2010). With reduced search costs, there is more of a “winner take all”
tendency. Increased speed of communication leads to both a greater advantage from
implementing new technology quickly, and a greater opportunity cost of waiting. Thus, in some
sectors, the profit-maximizing size of firms has increased and the number of firms with positive
economic profits has decreased. For a small firm to grow organically, it would have to devote
resources to hiring employees, developing markets, etc. A larger company might be able to
quickly redeploy existing employees and use its existing marketing network to develop profitable
markets more quickly.
4. Evidence from Post-IPO Mergers
If our hypothesis that the value of small independent firms has declined relative to the value
of larger firms is true, we would expect more private firms to sell out in trade sales and, for those
special report “For Richer, for Poorer” in the October 13, 2012 issue.
8
Another possible reason for the decline in profitability, especially for small firms and recent IPOs, is the change in
the accounting for employee stock option expenses. FAS123r became effective for fiscal years beginning after June
15, 2005 for large firms and after December 15, 2005 for small firms. We have not investigated the impact of this
accounting change on reported earnings. It is likely that this change would have a bigger impact in the technology
industry than in other industries due to the heavy use of employee stock options. Note, however, that the Table 2
downtrend in profitability was present before the accounting change.

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companies that do go public, a higher propensity to be involved in a merger as either an acquirer
or a target. If a lack of analyst coverage and high SOX compliance costs are important reasons
for why being a small publicly traded firm has become less attractive, we would expect an
increase in the last decade in the fraction of recent IPOs that subsequently go private as an
independent company.
Historically, venture capitalists have earned their biggest payoffs on portfolio companies
that have gone public (Smith, Pedace, and Sathe, 2011). In Figure 3, we show the percentage of
exits of VC-backed portfolio companies by IPOs (top) and by acquisitions (bottom) for
1990-2012. During all but the first two years of the sample period, the total number of exits is at
least 200 per year, with the number over 300 in every year from 1999-2012. Figure 3 reveals that
in 1990-2000, exits via IPOs and via trade sales were both common, although the percentage of
exits via a trade sale was rising. During 2001-2012, however, exiting via an IPO has become
uncommon. The patterns in Figure 3 are consistent with those reported in Poulsen and
Stegemoller (2008) for 1995-2004.
The patterns in Figure 3 are worth emphasizing, for they are inconsistent with some
alternative explanations of the lack of small company IPOs. As with the profitability of small
companies, there is no sudden change in 2000, but instead there is a steady increase in the
percentage of exits via trade sales during the 1990s. Furthermore, since it is rare for a VC-backed
company to have sufficient profitability and tangible assets to be a candidate for debt financing,
the increase in trade sales cannot be explained as a substitution of debt for equity financing. Thus,
the low interest rate environment in part of the last decade cannot be viewed as an important
reason for why venture capitalists are not taking their portfolio companies public.
Panel A of Table 3 reports the number of companies that were delisted for non-distress
reasons in the three years after going public for the IPO cohorts from 1980-2011. Of the 7,613

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IPOs from these years, 923, or 12.1%, either went private or were acquired within three years of
the IPO. Only 48 IPOs, or 0.6%, are involved in going private as a stand-alone company, and
only 81, or 1.1%, sold out to a private strategic buyer. Importantly, there is no evidence that the
propensity to go private either in a buyout or a trade sale increased in the last decade. By contrast,
790 of the 7,613 IPOs, or 10.3%, sold out to a publicly traded strategic buyer, and this
percentage increased from the 1980s for small company IPOs, as shown in Panel B of Table 3.
Table 3 also shows that the percentage of IPOs that are acquired within three years of going
public has increased over time. In 1980-1993, Panel A shows that there is only one IPO cohort
for which more than 10% of the firms are subsequently acquired by a strategic buyer, whether
public or private. In contrast, none of the IPO cohorts from 1994-2009 have less than 10% of the
firms subsequently acquired. The 2010-2011 cohorts have acquisition rates of less than 10%, but
a full three years after the IPO has not yet occurred for these cohorts at the time of our writing,
and the sample sizes are fairly small for these two cohorts.
Consistent with the economies of scope hypothesis, Brau and Fawcett (2006, Table II), in a
survey of 336 companies that went public in 2000-2002, report that the single most important
reason given for going public was an enhanced ability to make acquisitions. Arikan and Stulz
(2011), Brau, Francis, and Kohers (2003), Brau, Couch, and Sutton (2012), Celikyurt, Sevilir,
and Shivdasani (2010), Chemmanur, He, He, and Nandy (2011), Hovakimian and Hutton (2010),
and Hsieh, Lyandres, and Zhdanov (2011) all examine mergers around IPOs. Celikyurt, Sevilir,
and Shivdasani (Table 2) restrict their analysis to 1,295 IPOs from 1985-2004 that raised at least
$100 million ($2005) each, and report that 55% of the firms made at least one acquisition within
one year of the IPO, and that 74% of the companies made at least one acquisition within five
years of the IPO. Hovakimian and Hutton (2010, Table I) use 5,771 IPOs from 1980-2006 and
report that 19% of the firms made at least one acquisition within a year of the IPO. They also

14
show in their Figure 1 that the fraction of firms going public that subsequently made an
acquisition increased dramatically from the 1980s to the 1990s. Both Brau, Couch, and Sutton
(2012, Table 1) and Arikan and Stulz (2011, Table 2) confirm this pattern.
Using a sample of 3,457 IPOs from 1985-2003, Brau, Couch, and Sutton (2012, Table 1)
report that 33% of their sample made an acquisition during the first year after going public, with
the percentage at 20% or lower in 1985-1989, and above 20% in every year since then. Celikyurt,
Sevilir, and Shivdasani (2010, Table 2) point out that the average acquisition expenditures are
greater than those on either capital expenditures or research and development. Arikan and Stulz
(2011, Table 10) report that acquisitions of private firms by acquirers that recently went public
have an average announcement return of 1.38%. This positive announcement effect is consistent
with our hypothesis that small firms must grow fast to realize economies of scale and scope.
Our hypothesis that the reduction in small company IPOs is at least partly due to an increase
in economies of scale and scope produces a testable cross-sectional implication. If the changes in
economies of scale and scope are bigger in some industries than others, we predict that there
should be more M&A activity in those industries with a bigger increase. To test this implication,
we would need industry definitions and measures of which industries have seen the greatest
increase in the importance of economies of scope. Because increased merger activity might mean
a higher propensity to sell out in a trade sale prior to an IPO, the cross-sectional prediction for
IPO volume is less clear. In any case, we leave the testing of this implication for future work.
We can summarize the evidence in the above-mentioned studies of post-IPO acquisitions
and our Table 3 as showing that a large, and increasing, fraction of firms that do go public merge,
either as a target or an acquirer. Rather than depending on organic growth, these firms speed up
the process of achieving economies of scale and economies of scope through mergers.
Inconsistent with the regulatory overreach hypothesis, there has been no increase in the fraction

15
of recent IPOs that subsequently go private as an independent firm.
5. Has Sarbanes-Oxley Driven Away IPOs?
This section assesses the impact of the Sarbanes-Oxley of 2002 on U.S. and foreign IPOs,
shedding further light on the relevance of the regulatory overreach hypothesis.
5.1 The effect of SOX compliance costs on profitability
Section 404 of SOX has received widespread criticism for imposing large costs on small
public firms. Beginning in 2007, the SEC approved several delays to allow the smallest public
firms to postpone their compliance with Section 404(b), before permanently exempting them on
September 15, 2010 (SEC final rule #33-9142).
Since 2002, firms have had to pay SOX compliance costs. If the costs of complying with
SOX are sufficiently onerous that small firms are on net made worse off, the decline in small
company IPOs this decade can be partly attributed to SOX. Iliev (2010, p. 1163) estimates the
costs of compliance, and concludes that “On net, SOX compliance reduced the market value of
small firms.” In Figure 2, we plot the percentages of small and big seasoned firms with negative
EPS, as reported in columns 6 and 8 of Table 2. As can be seen, the uptrend in the fraction of
small companies reporting losses began before SOX. There is also an uptrend for big firms, but it
should be remembered that our definition of big firms ($250 million in annual inflation-adjusted
sales) includes many firms that would normally be classified as mid-cap or smaller.
Would there be more small firms with positive profits in the post-SOX period if
SOX-related costs had not boosted the expenses of publicly traded companies? To address this
question, we construct an alternative series of the percentage of unprofitable firms by assuming
after-tax SOX compliance costs of $650,000 per small firm and $2,536,000 per big firm,

16
dividing this number by the number of shares outstanding, and adding this back into EPS.9
For
example, a small firm with 10,000,000 shares outstanding would gain 6.5 cents per share if it
didn’t have this cost, and a big firm with 100,000,000 shares outstanding would gain 2.536 cents
per share. In Figure 2, we then show, for 2002 and later, the percentage of small (and big) firms
that would be profitable if they didn’t incur the extra SOX costs.
The effect on the profitability for small firms of paying the compliance cost is limited.
Adding the compliance cost back removes between 43 and 76 small firms’ EPS from the
negative EPS category each year. This only removes about 4% to 5% of the small firms from the
negative EPS group. The dotted line of Figure 2 shows that without paying any SOX compliance
costs, the firms’ profitability would be improved. It would still be the case, however, that for the
small seasoned firms, 40% or more of them would report negative EPS.
5.2 The effect of SOX on foreign listings
Many commentators have expressed concern over the decline in the relative importance of
U.S. equity markets in the last decade. If SOX is an important reason for why companies,
especially small companies, are not listing in the U.S., we might observe many U.S. companies
going public abroad. In contrast, if U.S. companies are not going public because the relative
advantage of being an independent firm has declined in comparison to becoming a part of a
larger organization, then we would not see a substitution of U.S. companies going public in
foreign markets rather than the U.S. In a Wall Street Journal article, Lucchetti (2011) states “In
9
Iliev (2010, p. 1166) uses a regression discontinuity approach and estimates that in 2004 small firms had
additional pre-tax audit costs of $697,890. Table 13 of the U.S. SEC report (2009a) reports mean compliance costs
for firms with at least three years of experience complying with SOX Section 404 for two periods: pre- and post-Nov.
15, 2007 for three categories of firms: those with a public float of $50-150 million, $150-700 million, and greater
than $700 million. The pre-tax pre- and post-2007 mean reported costs for small firms are $774,105 and $785,278.
For the moderate-size firms, the mean reported costs are $1,168,319 and $1,082,814, respectively. For the large
firms, the mean reported costs are $4,308,413 and $3,633,421, respectively. The $650,000 and $2,536,000 numbers
that we use are weighted averages of, respectively, the pre-, post-, and next- means in Panel A for small firms, and
Panels B and C for big firms, of Table 9 of the U.S. SEC (2009a) report. Next- refers to fiscal years in progress at
the time of the survey in 2009.

17
all, 74 U.S. companies have done IPOs in foreign countries since 2005, raising about $13.1
billion, according to Dealogic. That is a small fraction of the more than 650 U.S. companies that
have gone public on U.S. exchanges since 2005.” Of the $13.1 billion raised, $5 billion came
from the March 2006 IPO of KKR Private Equity Investors Ltd. on Euronext, which transferred
to the NYSE in 2008.
Further evidence that U.S. companies are not fleeing the U.S. to list in foreign markets is
contained in Doidge, Karolyi, and Stulz (2009, 2013). While they document that the market
share of the U.S., whether measured on the basis of the number of IPOs or the proceeds, has been
falling, they do not detect evidence that many firms that would have listed in the U.S. pre-SOX
are not doing so post-SOX.
In the 1990s, many large global IPOs were privatizations. In some countries, such as
Australia and Japan, many of the IPOs in recent years have been of very tiny companies (e.g., a
public float of $3 million). In London, main board listings have declined, although the number of
offerings on London’s Alternative Investment Market (AIM) was high before 2008. But most of
the AIM IPOs are essentially private placements to qualified institutional buyers (1,572 out of
1,642 IPOs) that never develop liquid trading (Vismara, Paleari, and Ritter, 2012, Table 2).
Our hypothesis that small firms are not going public in the U.S. because the advantage of
being a small independent firm has fallen applies to other countries as well. Consistent with this
hypothesis, Caglio, Hanley, and Marietta-Westberg (2012, Table X) report that both Germany
and France saw their domestic IPO volume drop by at least 50% in 2002-2007 relative to
1995-2001. Furthermore, the average IPO proceeds in Germany and France more than doubled,
indicating a loss of small deals, similar to the U.S. pattern. Doidge, Karolyi, and Stulz (2013,
Figure 1 and Table 8) also report a downtrend in IPO activity around the world, although they do

18
not emphasize this finding.10
Ritter, Signori, and Vismara (2012, Figure 2) document that M&A
activity in Europe has not declined, even though small company IPO volume has.
In Table 4, we report the percentage of foreign companies, including those using ADRs,
going public among U.S. IPOs each year from 1980-2012. Table 4 shows that the percentage of
foreign IPOs in the U.S. has not declined this decade. The market share of foreign companies
among U.S. IPOs has actually been increasing, partly due to the low number of U.S. companies
going public. During 2001-2012, there has been an annual average of 22 foreign company IPOs,
including 12 ADR IPOs.
To summarize, the evidence in our Table 4 and Doidge, Karolyi, and Stulz (2009, 2013)
does not suggest that the lower number of IPOs in the U.S. in recent years is because issuers are
fleeing U.S. markets in favor of foreign markets.
6. Analyst Coverage Following IPOs
In Section 3, we documented the poor post-IPO operating performance on small company
IPOs. We now examine the validity of one of the arguments underlying the regulatory overreach
hypothesis by presenting evidence on analyst coverage following IPOs. As previously discussed,
many commentators have argued that a decline in analyst coverage on small companies has
deterred these companies from going public.
The IPO ecosystem explanation for the decline of small company IPOs notes that more than
just the number of analysts has declined. Independent boutique investment banks such as L.F.
10
They report in their Table 8 that, exclusive of the U.S., in panel dataset regressions using 1990-2011 data with the
ratio of IPOs/listed companies in a country as the dependent variable, the coefficient on a measure of financial
globalization (a variable that is significantly positively correlated with a time trend) is insignificantly negative. In
regressions with scaled small firm IPO activity as the dependent variable (the mean, measured as percentage, is
about 1%), the sum of the coefficients on their world financial globalization variable and the interaction of this
variable with a non-US dummy is 1.359-1.656 = -0.297. The world financial globalization measure starts with a
value of 118% of world GDP in 1990 and increases in an almost monotonic manner to 366% in 2011.

19
Rothschild, Hambrecht & Quist, Robertson Stephens, and Alex. Brown, which were known as
the “Four Horsemen” in the 1980s, have disappeared. These underwriters, and Montgomery
Securities in the 1990s, took public hundreds of firms. In the late 1990s, commercial banks
seeking to expand into equity underwriting acquired almost all of the surviving boutiques, but
these banks have not taken public as many small companies per year, especially technology
companies. Proponents of the ecosystem explanation argue that small companies now have more
difficulty finding a reputable underwriter than had previously been the case.
Post-issue analyst coverage affects IPO volume if on average analyst coverage boosts a
company’s share price, lowering the required return as a public company relative to the required
return if the company continued to be private or was part of a larger corporation. This boost in
the share price would be reflected, everything else the same, in a higher market-to-book ratio and,
for companies with positive EPS, a higher price-to-earnings ratio. Evidence from existing event
studies shows positive stock market reactions to unexpected initiations of coverage and upgrades,
and negative stock market reactions to unexpected cessation of coverage or downgrades,
suggesting that analyst coverage does indeed boost the share price of a stock, at least temporarily
(see, e.g., Womack (1996, Table III), Irvine (2003, Table 1), Bradley, Jordan, and Ritter (2008,
Table 3), and Demiroglu and Ryngaert (2010, Table IV)).
In Table 5, we report the frequency of analyst coverage following IPOs. The main source
for analyst coverage data is the Institutional Brokers’ Estimate System (I/B/E/S) analyst
recommendation database. Since I/B/E/S recommendation data started during 1993, and we
examine the three years after issuing, the usable IPO sample in Table 5 is from 1994 to 2009. We
augment the one year post-IPO lead underwriter analyst coverage data with data from
Briefing.com, First Call, Investext, and Google Search, as well as some hand-collected Goldman
Sachs analyst reports from 1996 to 2000. For IPOs with no evidence of recommendations in a

20
year, we augment the dataset by examining the I/B/E/S earnings forecast database. If there is an
earnings forecast, we assume that the analyst making the forecast also covers the stock.11
We
restrict the sample to 3,682 IPOs with a midpoint of the original file price range no lower than $8.
Practitioners suggest that if an IPO has a lower than $8 midpoint value, there is usually little
demand from institutional investors. Most of the 386 IPOs with a file price range midpoint of
less than $8 are underwritten by low-prestige underwriters and frequently have no reported
analyst coverage.
Table 5 reports four analyst coverage ratios for small and large company IPOs. For instance,
in column 2, we report by year the percentage of firms that have at least one analyst report from
a lead underwriter by the end of the first anniversary of the IPO date. Columns 3, 4, and 5 report
the percentage of firms that have at least one analyst report from any sell-side analyst within the
first, second, and third year since the IPO date, respectively. The coverage ratio in the second and
third year is calculated conditional on the firm still being CRSP-listed at the start of the
respective year. The overall time series pattern in Table 5 suggests that there is little change in
the propensity to receive analyst coverage over time.
The relatively lower coverage ratios observed in 1994 and 1995 are more likely due to
incomplete data in I/B/E/S rather than a lack of analyst coverage in the earlier years. During
1994-2000, an (unreported) average of 96.6% of small company and 96.8% of large company
IPOs received coverage from at least one lead underwriter in the first year. During 2001-2009,
the respective averages are virtually identical at 95.3% of small company and 97.8% of large
company IPOs. There is close to universal post-IPO coverage by at least one analyst affiliated
with a lead underwriter. Of course, there is a selection bias issue—we do not observe the
11
This assumption is based upon talks with the former head of technology research at a bulge bracket investment
bank, Steve Balog, who said that he had never heard of an analyst making a formal EPS forecast on a company that
the analyst did not cover.

21
companies that didn’t go public because no underwriter would commit to providing analyst
coverage.
Lastly, it is worth noting that for almost all cohorts, a lower percentage of the surviving
IPOs are covered in year 2 than year 1, and in year 3 than in year 2. Partly this reflects a pattern
that as a company becomes more seasoned, it is either succeeding and thus generating interest
from institutional investors (and thus sell-side analysts), or it is failing and generating less
interest from institutional investors and analysts. In general, both the probability of adding
additional analysts covering the firm and the probability of becoming an “orphan” with no
coverage grows. Most importantly, for year 3 analyst coverage in column 5 of Table 5, there is
no evidence during our sample period of a downtrend for either small company or large company
IPOs, suggesting that of the companies that do go public, the risk of being abandoned by analysts
within a few years of going public has not increased.
In sum, our empirical results indicate no decline in post-IPO analyst coverage. Importantly,
these patterns are inconsistent with the argument that the drop in analyst coverage on small firms
has contributed to the near disappearance of small company IPOs. Consequently, a lack of
analyst coverage is not a plausible major cause of the decline in IPO volume.
7. Time-series Regressions Explaining Scaled IPO Activity
So far, we have presented univariate evidence consistent with our hypothesis that the
increasing importance of economies of scope and speed in bringing products to market is an
important determinant of the decline in IPOs, particularly among small firm IPOs. In this section,
we conduct time-series regressions using scaled quarterly IPO activity as the dependent variable.
The economies of scope hypothesis predicts a long-term steady decline in IPO volume,
especially for small company IPOs, whereas the regulatory overreach hypothesis predicts a

22
discrete drop after SOX was implemented and/or a downtrend starting in May 1994 when
bid-ask spreads began to fall.
Figure 4 depicts the time variation in the scaled quarterly volume of small and large firm
IPOs over the 1975 to 2012 period. Figure 4 also shows the Shiller P/E ratio, calculated as the
ratio of the level of the S&P 500 divided by the average value of inflation-adjusted annual
earnings over the prior ten years. Inspection of Figure 4 shows that scaled IPO volume began to
fall below what might be expected based on market valuations starting in 1997, and did not
recover following the stock market rally beginning in the spring of 2003.12
To test the predictions of the regulatory overreach and economies of scope hypotheses, we
estimate the following regression where we use four measures of quarterly IPO volume as the
dependent variable: Model 1: IPOs/Real GDP, Model 2: Small firm IPOs/Real GDP, Model 3:
Large firm IPOs/Real GDP, and Model 4: Small firm IPOs/IPOs:
1 2 3 , 3
4 1, 4 5 4
6 2 7 2, 1 8
IPOVolume Time trend SOXdummy Real GDP growth
Future Nasdaq return Closed-end fund discount
LogM/Bfor small firms Nasdaq return IPOinitial retu
t t t
t t t
t t t
α β β β
β β
β β β
+
+ + −
− − −
= + × + × + ×
+ × + ×
+ × + × + ×
( ) ( )
1
9 1 10
2
1
rn
Percentage of small public firms with negative EPS Quarter 1 dummy ,
, 0, . 2
t
t t
t t t t
u u N
β β ε
ε ρ ε σ
−
−
−
+ × + × +
= × + :
Panel A of Table 6 reports the quarterly time series regression results using maximum
likelihood estimation with a first-order autoregressive error term AR(1), estimated over the 1975
to 2011 period.13
We scale IPO volume by real GDP in Models 1 through 3 based on the
assumption that the number of IPOs should be proportional to the size of the economy. In Model
4, the dependent variable is the ratio of small firm IPO volume to total IPO volume, and thus is
12
If the market-to-book ratio on Compustat- and CRSP-listed small firms (using $250 million of $2009 as the
cutoff) is used instead of the Shiller P/E ratio, as we have done in unreported results, the patterns look very similar.
13
Data on small firm earnings is not comprehensibly available before 1975, especially in the pre-Nasdaq years
before February 1972 when most IPOs were traded over-the-counter.

23
not influenced by changes in real GDP. As before, we define small and large firm IPOs on the
basis of a cutoff of pre-IPO last twelve month sales of $50 million ($2009). Approximately 50%
of IPOs fit into each of these two categories. Thus, if the effect of a variable is the same on small
and large firm IPOs, the coefficients in Models 2 and 3 should be of the same order of magnitude,
and these coefficients should be half as big as in Model 1.
Our specification nests the economies of scope and regulatory overreach hypotheses. We
use a time trend variable to capture the impact on scaled IPO volume of a gradual change in the
importance of economies of scope and speed to the product market.14
A negative coefficient on
the time trend would suggest that IPO volume experiences a continuous decline, just as
Campbell, Lettau, Malkiel, and Xu (2001) use a time trend to test for a gradual increase in
idiosyncratic stock volatility. In contrast, if excessive regulatory costs are a cause of the low IPO
volume observed in the last decade, a dummy variable for this period should have a significant
negative coefficient. The SOX dummy equals zero before the third quarter of 2002 and equals
one until after the fourth quarter of 2007, when small firms were given exemption from some
compliance costs. This dummy variable is intended to capture the impact of SOX on IPO volume
after SOX was enacted on July 30, 2002.15
Following Lowry (2003), our regression specification incorporates controls for capital
demands (real GDP growth), investor sentiment (future Nasdaq returns and the closed-end fund
discount), stock market conditions (lagged Nasdaq returns, the log of the small firm
market-to-book ratio, and lagged IPO average first-day returns), and a first-order autoregressive
14
Ideally, we would use a direct measure of the importance of economies of scope and scale. One possible measure,
the aggregate number of patents granted, suffers from confounding effects associated with changes in patent laws
and their implementation that occurred during our sample period.
15
The decline in analyst coverage story would suggest a more continuous change in small company IPO volume,
with discrete changes associated with the decline in Nasdaq bid-ask spreads starting in May 1994, the S.E.C.’s 1997
Order Handling Rules, the implementation of Reg FD in October 2000, decimalization occurring in 2001, and the
Global Settlement in April 2003. See Weild and Kim (2008, 2009) for further details.

24
error term.16
At the core of our empirical findings is a negative coefficient on the time trend for small
firm IPOs (Model 2) as well as the ratio between small firm IPOs and total IPOs (Model 4). For
Model 2, the coefficient of -4.62 (with a t-statistic of -2.01) on the time trend implies that by the
end of our sample period, the quarterly volume of small firm IPOs per trillion dollars of annual
real GDP declines by 5.87 (-4.62×0.01 trend per quarter×127 quarters) from the beginning of
1980.17
Compared with a sample average of 2.74 for the scaled quarterly small firm IPO volume
(reported in Panel B of Table 6), the time trend is economically significant, with 352 (5.87×4
quarters per year×$15 trillion in GDP) fewer small company IPOs in 2011 than would otherwise
have occurred. For large firm IPOs, the time trend coefficient of -3.12 (t-statistic=-1.74) implies
a decline from 1980 to 2011 of 3.96 scaled IPOs per quarter, with 238 fewer large firm IPOs in
2011 than would otherwise have occurred. The Model 4 estimate of the time trend is also
statistically significant and negative, corroborating the finding that small firm IPOs exhibit a
stronger downtrend than large firm IPOs, in line with our hypothesis that the increased
importance of economies of scale and scope exert a greater adverse impact on small firm IPOs.18
Inconsistent with the regulatory overreach hypothesis, the SOX dummy is never statistically
16
The coefficients of approximately 0.50 on the autoregressive error term in our regressions using 1975-2011 data
are substantially lower than the approximately 0.80 reported by Lowry (2003, Table 3) using 1972-1996 data. Pastor
and Veronesi (2005, Table VI) report first-order autoregressive coefficients of over 0.80 for their 1960-2002 sample
period. All three studies use scaled quarterly IPO volume as the dependent variable. The lower residual
autocorrelation in our regressions is primarily due to our inclusion of a time trend, the use of a logged M/B ratio
rather than an unlogged ratio, and deflating quarterly IPO volume by real GDP rather than the number of
CRSP-listed firms.
17
We choose 1980 as the beginning of the trend representing an increase in the speed of technological change based
on evidence discussed in the Economist magazine’s special report “For Richer, for Poorer” in the October 13, 2012
issue. In discussing the time trends in the intra-country and global Gini coefficients, on page 9 of the survey the
Economist states “But around 1980 both these trends went into reverse.”
18
As an alternative to a simple time trend, in unreported results we also use a measure of the productive efficiency
of big firms relative to small firms, computed on an annual basis as the equally weighted average bias-adjusted
frontier efficiency of big firms minus the average for small firms using firm-specific data supplied by Leverty and
Qian (2010). This measure has an insignificant negative coefficient, consistent with fewer small company IPOs
when the efficiency of big firms is high in comparison to small firms. This measure, which is available only from
1988-2010, is positively correlated with the time trend.

25
significant in the presence of the time trend and our control variables. For instance, for Models 2
and 4, the estimates of the SOX dummy are -0.40 and -0.06, with t-statistics of -0.40 and -0.98,
respectively. Such a finding compliments our Table 4 evidence regarding international listings
and the Figure 2 evidence on profitability changes, which suggest that the impact of SOX is
insufficiently large to account for much of the observed decline in IPO volume. Weild and Kim
(2009) and Doidge, Karolyi, and Stulz (2013, Figure 4) also report evidence that U.S. IPO
activity started to fall below what would be expected starting five years prior to the passage of
SOX and the Global Settlement.
In sum, the regression evidence is supportive of the economies of scope hypothesis. In
particular, the negative time trend estimates support our argument that the increased importance
of economies of scope and speed is a driver of the decline in IPO volume since the 1996 peak,
especially for small firms, suggesting that small firms are particularly vulnerable to changes in
technology.
8. Small Company IPOs Underperform in the Long Run
Section 3 of this article documented a decline over time in the profitability of small firms
conducting IPOs. We now turn to the post-issue stock return performance of small and large
company IPOs, and link it to the economies of scope and regulatory overreach hypotheses.
Table 7 tabulates the first-day return and three alternative measures of the three-year
buy-and-hold returns after the IPO issue date for all IPOs, small company IPOs, and large
company IPOs. Three-year buy-and-hold returns are measured from the closing market price on
the first day of trading until the earlier of either their three-year anniversary or their delisting date.
The buy-and-hold abnormal return BHARi,T for stock i over horizon T is measured both with
respect to the CRSP value-weighted index (market-adjusted), and with respect to a seasoned

26
stock that is matched on the basis of market capitalization and its book-to-market ratio
(style-adjusted):
( )
min(T, delist) min(T, delist)
, , ,
1 1
(1 ) (1 ), 1
i T i t M t
t t
BHAR R R
= =
= + − +
∏ ∏
where Ri,t is the net return in period t on stock i and Ri,t is the net return in period t on either the
value-weighted market or the style-matched seasoned firm.19
Table 7 reports that the average IPO from 1980-2009 has underperformed its style-matched
counterpart by 7.2% in the three years after going public. Inspection of the bottom two rows
shows that small company IPOs have underperformed their style-matched benchmark by an
average of 17.3% during the three years after going public, whereas large company IPOs have
outperformed their style-matched benchmark by 3.1%. Furthermore, small company IPOs have
underperformed their style-matched benchmark in every subperiod. The underperformance
relative to the value-weighted market benchmark is even more severe for the small companies,
and is also present in every subperiod.
The underperformance of small company IPOs has not been restricted to the United States.
Vismara, Paleari, and Ritter (2012, Table 5) report an average three-year buy-and-hold abnormal
return of -27.5% for European IPOs from 1995-2008 with pre-IPO annual sales of less than €30
million.
19
For the style-matched returns, each IPO with a book-to-market ratio higher than zero is matched with a
nonissuing firm in the same size decile (using NYSE firms only for determining the decile breakpoints) having the
closest book-to-market ratio. Each IPO with a zero or smaller book-to-market ratio is matched with a nonissuing
firm of a book-to-market ratio of zero or smaller having the closest market capitalization. For the IPOs,
book-to-market ratios are calculated using the first recorded post-issue book value and the post-issue market cap
calculated using the closing market price on the first CRSP-listed day of trading. For nonissuing firms, the
Compustat-listed book value of equity for the most recent fiscal year ending at least four months prior to the IPO
date is used, along with the market cap at the close of trading at month-end prior to the month of the IPO with which
it is matched. Nonissuing firms are those that have been listed on the Amex-Nasdaq-NYSE for at least five years,
without issuing equity for cash during that time. If a nonissuer subsequently issues equity, it is still used as the
matching firm. If a nonissuer gets delisted prior to the delisting (or the third anniversary), the second-closest
matching firm on the original IPO date is substituted, on a point-forward basis. For firms with multiple classes of
stock outstanding, market cap is calculated using the first closing market price and the total number of shares
outstanding across all classes of stock as reported in Compustat. Seasoned firms with multiple classes of stock are
excluded as potential matching candidates.

27
Even though there have been relatively few small company IPOs during the 2001-2009
period, they have nevertheless subsequently underperformed, by an average of 30.3% on a
style-adjusted basis. Furthermore, small company IPOs have lower average first-day returns than
large company IPOs during 2001-2009, reversing the historical relation. In sum, small company
IPOs from 2001-2009 have continued to yield inferior returns for their public market investors.
The poor long-run performance of small company IPOs, in principle, could be consistent
with both the regulatory overreach hypothesis and the economies of scope hypothesis. If a drop
in analyst coverage and SOX compliance costs were unanticipated, companies that were already
public when these changes occurred would see low returns as investors incorporated the effects
into market prices. Table 7, however, reveals low long-run returns on small company IPOs in all
subperiods over our 30 year sample period.
The economies of scope hypothesis asserts that technological change has put increasing
pressure on the profitability of small firms over a prolonged period of time. The declining
profitability of small firms would result in low returns for investors, however, only if the decline
in profitability was unanticipated. Irrespective of the cause of the low realized returns on small
company IPOs, the low post-issue returns inevitably would dampen investor enthusiasm for
small company IPOs, resulting in fewer offerings.
9. Alternative Explanations: Litigation Risk and Public Market Valuations
Additional explanations for the decline in IPO activity beyond those that we have discussed
have been offered by Angel (2011) and others.
9.1 Litigation risk
The litigation environment in the U.S. imposes substantial costs on public firms. However,
litigation costs are unlikely to explain the dramatic decline of small company IPOs. According to

28
the Class Action Filings Index published by the Securities Class Action Clearinghouse at
Stanford Law School in cooperation with Cornerstone Research, the annual number of class
action filings has not increased in recent years.20
Specifically, the average annual number of
“classic” securities class actions in 1997-2000 is 210, while the average in 2001-2011 is 187.21
Thus, we are unable to find evidence that increased litigation risk for public firms has had a
greater deterrent effect on potential IPOs in recent years than in the 1990s.
9.2 Public market valuations
Many articles have documented that there are more IPOs when public market valuations are
high (e.g., Lerner (1994, Figure 1) and Lowry (2003, Tables 3 and 4)). This “valuation” view
generates the prediction that IPO volume will recover to the lofty levels of the 1980s and 1990s
if and when public equity market valuations recover to their previous peaks. Part of the high
volume of IPOs in the late 1990s could thus be attributable to the unsustainably high market
valuations on technology stocks. In our Table 6 time-series regressions, our main control for
valuation levels is the natural logarithm of the market-to-book ratio for small stocks.
During the eleven years from 1990-2000, the quarterly average market-to-book ratio for small
firms, lagged by two quarters, was 3.89. During the eleven years from 2001-2011, this same
measure averaged 3.16. Using the coefficient of 3.33 on the logged market-to-book ratio for
small stocks in Model 1 of our Table 6 regressions, the drop in the average market-to-book ratio
implies 3.33×[ln(3.89)-ln(3.16)] = 0.692 fewer IPOs per quarter per trillion dollars of real GDP,
or 42 fewer IPOs per year with $15 trillion of annual GDP. Thus, the market conditions
hypothesis can partly explain why IPO volume in 2001-2011 has been lower than previously, but
20
See http://securities.stanford.edu/companies.html for details on this index.
21
The Class Action Filings Index excludes “IPO allocation” lawsuits, mainly because these complaints do not
allege that the IPO firms are engaged in any frauds in their own business or financials. Including the IPO allocation
lawsuits adds 312 filings in 2001 and 1 filing in 2002, but has no impact in other years. Classic lawsuits also exclude
a total of 93 sell-side analyst lawsuits and mutual fund lawsuits, neither of which target operating companies.

29
most of the decline is left unexplained.
Pástor and Veronesi (2005) develop a model in which firms receive a positive NPV
investment opportunity and wait for the optimal time to go public, resulting in an increase in IPO
volume following market rises. Following market rises, there is a relatively low stockpile of
firms waiting to go public, and several periods of low volume may follow. Their theoretical
model, however, restricts the strategy space to either waiting or going public, with no option to
sell out in a trade sale in order to realize the NPV before the investment opportunity disappears.
Furthermore, the model would seem to predict 1) large increases in IPO volume during the bull
market starting in March 2003 and peaking in October 2007, following a multi-year lull in IPO
activity, and large increases in IPO volume in the bull market starting in March 2009 and
continuing as of December 2012 following another long lull in IPO activity, and 2) many IPOs
beginning a few years after the huge capital commitments made to venture capital funds in 2000.
In Appendix Table A-2, we expand our Table 6 regression model to include two additional
variables: 1) the interaction of the lagged one-quarter Nasdaq return and a dummy variable for
whether IPO volume during the previous eight quarters had been low, and 2) the average value of
capital commitments made to venture capital funds scaled by GDP in years -3 to -6. Inspection of
the table discloses very modest explanatory power for these variables, and the coefficient on
lagged VC activity is insignificantly negative instead of being positive (more VC investment
should result in more IPOs a few years later). The downtrend in small company IPO volume
predicted by the economies of scope hypothesis persists, although it becomes less significant due
to the high correlation of the time trend and lagged VC activity (ρ=0.71). Thus, the Pástor and
Veronesi (2005) market conditions model is not effective at explaining the IPO drought that
began in 2001 that, as of 2013, shows no signs of ending.
9.3 Other multi-year droughts in IPO activity

30
The 2001-2012 IPO drought in the U.S. is not the first time that there has been a multi-year
drought in IPO activity. As documented in Gompers and Lerner (2003) and Pástor and Veronesi
(2005), from 1930-1945 there were very few IPOs in the U.S., as was the case in 1963-1967 and
1973-1980. If long droughts are common, why is a new explanation needed to explain the
2001-2012 drought?
The drought of the 1930s and 1940s, we would conjecture, is easily explained by the Great
Depression and World War II, a period in which inflation-adjusted stock prices were
continuously at less than half of their 1929 levels.22
The 1973-1980 drought also saw
inflation-adjusted stock prices at 40% or more below their 1972 levels. Unlike the other two
droughts, stock prices were not depressed in the 1963-67 drought, which saw an average of 63
IPOs per year, according to Gompers and Lerner (2005, Table 1). U.S. real GDP was less than
one-third as large in 1963-1967 as in 2001-2012, however, so the 1963-1967 drought still had the
equivalent of 200 IPOs per year, and it only lasted for five years. In addition to the length of the
current drought, a further difference with the droughts of the 1960s and 1970s is that, unlike
today, there was no large private equity industry looking for exits for their portfolio companies.
Thus, the current IPO drought is fundamentally different than the prolonged droughts of
1930-1945 and 1973-1980, when a depressed stock market was associated with low IPO volume.
10. Conclusions
During 1980-2000, an average of 310 IPOs occurred each year in the U.S., but this has
fallen to an average of only 99 IPOs per year during 2001-2012. Even more dramatically, an
average of 165 small company (pre-IPO inflation-adjusted annual sales of less than $50 million)
22
See Robert Shiller’s web site, where the ratio of the S&P 500 to the Consumer Price Index is reported on a
monthly basis.

31
IPOs occurred each year, and this number has dropped by more than 80% to an average of only
28 deals per year during 2001-2012.
Many commentators have argued that SOX compliance costs and a decline in the IPO
“ecosystem” of underwriters focusing on technology stocks and providing analyst coverage are
the main reasons for why small company IPOs have been uncommon in the U.S. since 2000.
Although we do not dispute that the 2002 Sarbanes-Oxley Act and the 2003 Global Settlement
have reduced the attractiveness of being public for small companies, this regulatory overreach
hypothesis is unable to explain many facts, and many of its predictions are not supported.
Our economies of scope hypothesis posits that there has been a fundamental change in
many sectors of the economy whereby the importance of bringing products to market quickly has
increased. Our explanation predicts that independent small companies will have lower profits
relative to their potential profits generated as part of a larger organization that can realize
economies of scope and rapidly expand production. If this explanation is correct, fewer firms are
going public and staying independent because greater value is created in a sale to a strategic
buyer in the same or a related industry.
We report that among small firms, the percentage of IPOs from the prior three years that are
unprofitable was below 60% in every year from 1980-1997, and has been above 60% in every
year since then. Furthermore, the post-IPO abnormal returns earned by investors on small
company IPOs have been low, underperforming a style benchmark by an average of 17.3% in the
three years after going public, compared to outperformance of 3.1% for large company IPOs. Of
those companies that do go public, many are subsequently involved in M&A deals, either as a
target or an acquirer. The evidence is consistent with an environment of “eat or be eaten,” where
slow organic growth as an independent company is less attractive than quickly achieving
economies of scale and scope via making acquisitions or by being acquired.

32
In addition to providing univariate evidence supporting our economies of scope hypothesis,
we report the results of time series regressions with the quarterly volume of IPOs scaled by real
GDP as the dependent variable and a number of control variables present. Consistent with our
economies of scope hypothesis, there is a negative time trend in scaled IPO volume, and the
effect is economically and statistically more pronounced for small company IPOs than for large
company IPOs. Furthermore, a dummy variable for the period after SOX was implemented in
July 2002 is economically and statistically indistinguishable from zero, inconsistent with the
regulatory overreach hypothesis.
If we are right, regulatory changes aimed at increasing the number of IPOs are likely to
have minor effects, since the decline in IPOs is not due to a broken IPO market, but because
small independent companies are not necessarily the profit-maximizing form of organization.
Consequently, IPO volume is unlikely to return to the levels that were common in the 1980s and
1990s. Even more important from a public policy perspective, if our economies of scope
hypothesis is correct, encouraging small firms to remain independent rather than realize greater
value as part of a larger organization might harm the economy.

33
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38
Table 1
Number of IPOs Categorized by the Last Twelve Month (LTM) Sales, 1980-2012
The sample of 7,707 initial public offerings excludes IPOs with an offer price below $5, unit
offers, ADRs, closed-end funds, REITs, SPACs, bank and S&L IPOs, limited partnerships, small
best efforts offers, and firms not listed on CRSP within six months of the offer date. Small and
large firm IPOs are categorized on the basis of the last twelve month (LTM) sales prior to the
IPO, expressed in terms of 2009 purchasing power. Two IPOs with missing LTM sales are placed
in the less than $50 million in sales category. Proceeds are in billions of dollars (2009 purchasing
power), and represent the aggregate amount raised by issuing firms and selling shareholders in
all of the IPOs, excluding overallotment options that get exercised. *
indicates that the change
from 1980-2000 to 2001-2012 is statistically significant at the 1% level assuming autocorrelated
and heteroscedastic error terms. ψ
indicates that the decrease in small firm IPOs is greater than
the decrease in large firm IPOs at the 1% level in seemingly unrelated regressions (SURs) with
autocorrelated and heteroscedastic error terms.

39
Period
No. of
IPOs
No. of IPOs Percentage of IPOs Total Proceeds
small firms large firms small firms large firms ($ billions)
1980 73 38 35 52% 48% $2.4
1981 196 137 59 70% 30% $5.7
1982 78 55 23 69% 31% $2.2
1983 451 275 176 61% 39% $19.2
1984 175 96 79 55% 45% $4.5
1985 185 91 94 49% 51% $8.8
1986 391 187 204 48% 52% $25.6
1987 283 124 159 44% 56% $22.0
1988 102 40 62 39% 61% $6.8
1989 113 44 69 39% 61% $9.1
1990 110 43 67 39% 61% $7.1
1991 286 107 179 37% 63% $24.1
1992 412 181 231 44% 56% $34.7
1993 510 221 289 43% 57% $46.7
1994 404 201 203 50% 50% $25.0
1995 461 243 218 53% 47% $41.4
1996 676 396 280 59% 41% $57.6
1997 474 252 222 53% 47% $42.1
1998 282 140 142 50% 50% $44.0
1999 477 329 148 69% 31% $83.2
2000 381 274 107 72% 28% $81.1
2001 79 24 55 30% 70% $41.3
2002 66 13 53 20% 80% $26.3
2003 62 14 48 23% 77% $11.1
2004 174 67 107 39% 61% $35.7
2005 160 44 116 27% 73% $31.3
2006 157 48 109 31% 69% $32.5
2007 160 55 105 34% 66% $37.2
2008 21 4 17 19% 81% $22.8
2009 41 4 37 10% 90% $13.2
2010 92 21 71 23% 77% $29.1
2011 81 22 59 27% 73% $25.9
2012 94 19 75 20% 80% $29.2
1980-2012 7,707 3,809 3,898 49% 51% $928.9
Annual Averages:
1980-2000 310 165 145 53% 47% $28.3
2001-2012 99* 28* 71*,ψ
28% 72% $28.0
1980-2012 234 116 118 49% 51% $28.1

40
Table 2
Profitability of Recent IPOs and Seasoned Firms by Fiscal Year, 1980-2011
This table reports the percentage of recent IPOs and seasoned publicly traded firms with negative
earnings per share (EPS) each year. Columns 1-4 are for IPOs and columns 5-8 are for seasoned
firms. In columns 1-4, for fiscal year t we use IPOs where year t is one of the first three post-IPO
fiscal years, with the first post-IPO fiscal year ending at least 6 months after the IPO. Small and
large firms are defined, for columns 1-4, on the basis of pre-IPO annual sales of $50 million
($2009), and for columns 5-8, on the basis of fiscal year sales of $250 million ($2009). For example,
there are 25 small company IPOs for which fiscal year 1980 is one of their first three post-IPO
fiscal years, and 28% of these 25 companies had negative earnings in fiscal 1980. For companies
with at least three years of seasoning, fiscal 1980 has 1,449 firms with less than $250m ($2009) in
sales, with 21% of these firms having negative earnings. For the annual averages, the percentages
are weighted by the number of observations, and do not equally weight each year.

41
All CRSP/Compustat firms with
IPOs from the prior 3 years at least 3 years trading history
small firm IPOs large firm IPOs small firms large firms
Fiscal No. EPS<0 No. EPS<0 No. EPS<0 No. EPS<0
Year (1) (2) (3) (4) (5) (6) (7) (8)
1980 25 28% 45 2% 1,449 21% 1,762 6%
1981 80 29% 76 8% 1,443 24% 1,698 8%
1982 178 34% 103 17% 1,639 32% 1,590 13%
1983 228 46% 121 21% 1,722 34% 1,562 11%
1984 415 44% 230 10% 1,856 37% 1,563 10%
1985 383 41% 254 17% 1,879 43% 1,491 14%
1986 384 42% 305 21% 2,144 46% 1,489 16%
1987 342 43% 366 17% 2,180 45% 1,506 14%
1988 346 40% 395 16% 2,160 45% 1,525 13%
1989 262 44% 323 22% 2,347 46% 1,595 15%
1990 174 49% 247 24% 2,507 46% 1,638 18%
1991 119 44% 203 24% 2,535 47% 1,647 21%
1992 251 51% 343 19% 2,531 44% 1,695 17%
1993 353 55% 494 17% 2,864 40% 1,782 17%
1994 522 54% 671 13% 2,905 40% 1,892 11%
1995 527 53% 632 19% 2,964 39% 2,019 14%
1996 674 55% 655 20% 3,203 40% 2,212 14%
1997 759 58% 605 22% 3,317 41% 2,342 14%
1998 763 63% 630 25% 3,280 45% 2,429 18%
1999 583 66% 514 32% 3,340 47% 2,526 17%
2000 636 82% 423 42% 3,271 48% 2,526 20%
2001 542 91% 288 52% 3,215 53% 2,453 28%
2002 385 87% 233 49% 3,180 51% 2,476 24%
2003 146 77% 156 30% 3,162 48% 2,504 21%
2004 61 80% 153 14% 2,880 45% 2,584 14%
2005 86 67% 206 16% 2,657 44% 2,581 14%
2006 130 72% 276 17% 2,444 45% 2,544 13%
2007 136 72% 299 24% 2,372 48% 2,490 16%
2008 121 76% 272 35% 2,318 57% 2,489 31%
2009 74 74% 182 36% 2,332 61% 2,467 26%
2010 37 65% 130 24% 2,244 51% 2,540 17%
2011 47 72% 168 26% 2,066 47% 2,498 17%
Annual Averages:
1980-1989 264 42% 222 17% 1,882 39% 1,578 12%
1990-1998 460 56% 498 20% 2,901 42% 1,962 16%
1999-2000 610 75% 469 37% 3,305 47% 2,526 19%
2001-2011 160 82% 215 30% 2,625 50% 2,511 20%
1980-2011 305 59% 312 23% 2,513 45% 2,066 17%

42
Table 3
Acquisitions and Buyouts of Recent IPOs, 1980-2011
In this table, we merge our IPO database with the CRSP delisting file and the target firms in the
Thomson Reuters (SDC) M&A database. The delisting file gives us the delisting date and the
M&A file gives us information on the identity of the acquirers. We classify M&A deals via the
following screens. First, the SDC M&A deal has to be completed with an effective date after the
IPO date. The effective date must be within 200 calendar days before or after the CRSP delisting
date. Second, the delisted IPO must have an effective date of being acquired that is no more than
three years after the IPO date. This leaves us with 819 M&A deals targeting IPO firms in both
the CRSP delisting and SDC M&A databases. Third, we identify each deal by searching SDC,
CRSP, Compustat, Bloomberg, Wikipedia and other sources to classify acquirers into four
categories: 1) strategic and public, 2) strategic and private, 3) financial and public, and 4)
financial and private.
In Panel A, if the deal is identified as a leveraged buyout (LBO) and the acquirer is a special
purpose acquisition company (SPAC), then the deal is labeled as financial and public. Two kinds
of acquirers are classified as financial and private. If the deal is identified as an LBO and the
acquirer is not a SPAC, the deal is classified as financial and private. If the deal is not identified
as an LBO, but the deal type is classified as going private in SDC and the acquisition name is
identified as a private company, usually whose name includes "LP", "LLC", or "acquisition", the
deal is identified as financial and private. The rest of the deals are identified as strategic. For the
strategic deals, if the acquirer is a public company, listed in the US or overseas, or is a subsidiary
of a public company, then it is strategic and public. Otherwise, it is classified as strategic and
private. For the strategic buyer, if the acquirer is an investor group, we classify the deal as public
if at least half of the investors we can identify are public, otherwise it is classified as private. For
the 92 IPOs that are identified by CRSP as delisted for non-distress reasons but are not in the
SDC M&A database, we search EDGAR and other sources and identify one deal as financial and
private and the other 91 as strategic and public. The Percentage of Strategic Buyers includes both
public and private strategic buyers.
In Panel B, we categorize IPOs into small and large company IPOs based on their pre-IPO last
twelve months sales ($2009). Based on CRSP delisting codes, all companies that were either
acquired by a strategic buyer or by a buyout firm are classified as mergers, since buyout firms
typically set up an acquisition vehicle to merge the public company into.

43
Panel A: Acquisitions and Buyouts of Recent IPOs
No. of cohort IPOs Number of acquisitions and buyouts by
No. of delisted for Strategic buyer Financial buyer
Year IPOs non-distress reasons Public Private Percentage Public Private
1980 73 2 2 0 2.7% 0 0
1981 196 13 11 1 6.1% 0 1
1982 78 6 4 2 7.7% 0 0
1983 451 29 27 2 6.4% 0 0
1984 175 16 14 2 9.1% 0 0
1985 185 18 14 2 8.6% 0 2
1986 391 40 31 5 9.2% 0 4
1987 283 44 26 4 10.6% 0 14
1988 102 7 7 0 6.9% 0 0
1989 113 8 8 0 7.1% 0 0
1990 110 5 4 1 4.5% 0 0
1991 286 9 6 3 3.1% 0 0
1992 412 36 34 2 8.7% 0 0
1993 510 44 38 4 8.2% 0 2
1994 404 42 37 4 10.1% 0 1
1995 461 79 72 6 16.9% 0 1
1996 676 115 101 11 16.6% 0 3
1997 474 82 69 6 15.8% 0 7
1998 282 40 33 3 12.8% 0 4
1999 477 106 96 8 21.8% 0 2
2000 381 56 51 4 14.4% 0 1
2001 79 8 8 0 10.1% 0 0
2002 66 11 10 1 16.7% 0 0
2003 62 8 7 0 11.3% 0 1
2004 174 24 21 0 12.1% 2 1
2005 160 24 19 4 14.4% 0 1
2006 157 19 16 1 10.8% 0 2
2007 160 18 14 2 10.0% 2 1
2008 21 3 3 0 14.3% 0 0
2009 41 6 4 1 12.2% 0 1
2010 92 5 3 2 5.4% 0 0
2011 81 0 0 0 0.0% 0 0
1980-2011 7,613 923 790 81 11.4% 4 48
Panel B: Frequency of Being Acquired or Going Private within Three Years of the IPO
Small firm IPOs (sales<$50m) Large firm IPOs (sales >$50m)
Period IPOs Mergers Merger rate IPOs Mergers Merger rate
1980-1989 1,087 65 6.0% 960 118 12.3%
1990-1998 1,784 206 11.5% 1,831 246 13.4%
1999-2000 603 126 20.9% 255 36 14.1%
2001-2011 316 41 13.0% 777 85 10.9%
1980-2011 3,790 438 11.6% 3,823 485 12.7%

44
Table 4
The Market Share of Foreign Companies among U.S. IPOs, 1980-2012
This table includes American Depositary Receipts (ADRs) as well as other IPOs, and so has a
higher total number of IPOs than those annual volumes reported in Table 1. In other words, the
number of IPOs in Table 1 is computed as: Domestic + Total Foreign – ADRs. For example, the
1988 sample size of 102 (as shown in Table 1) = 100 + 10 – 8. We continue to exclude IPOs with
an offer price below $5.00 per share, unit offers, SPACs, REITs, closed-end funds, partnerships,
banks and S&Ls, small best efforts IPOs, and IPOs not listed on CRSP (this last screen limits the
sample to NASDAQ, Amex, and NYSE-listed issues) within six months of the offer date.
Bermuda-domiciled companies are included as foreign, irrespective of the main country of
operations. Bermuda, Canada, China, Greece, Israel, the Netherlands, and the United Kingdom
are the most common countries for IPOs that list in the U.S. Dealogic is the main source of
information on foreign IPOs, because the Thomson Reuters (SDC) new issues database
frequently classifies a follow-on offering that simultaneously includes a U.S. listing as an IPO, as
does the NYSE. We have deleted at least 88 of these listings from the IPO counts. The count for
Chinese IPOs does not include those from Hong Kong, and excludes “reverse mergers” and best
efforts IPOs.

45
Year
Number
of IPOs Domestic
Foreign Chinese
Total ADRs % Foreign Total ADRs % Chinese
1980 73 71 2 0 2.7% 0 0 0%
1981 196 191 5 0 2.6% 0 0 0%
1982 78 77 1 0 1.3% 0 0 0%
1983 451 447 4 0 0.9% 0 0 0%
1984 176 171 5 1 2.8% 0 0 0%
1985 185 182 3 0 1.6% 0 0 0%
1986 392 390 2 1 0.5% 0 0 0%
1987 283 279 4 0 1.4% 0 0 0%
1988 110 100 10 8 9.1% 0 0 0%
1989 119 110 9 6 7.6% 0 0 0%
1990 111 107 4 1 3.6% 0 0 0%
1991 289 278 11 3 3.8% 0 0 0%
1992 417 394 23 5 5.5% 0 0 0%
1993 529 488 41 19 7.7% 1 1 0.2%
1994 423 387 36 19 8.5% 3 2 0.7%
1995 478 435 43 17 9.0% 1 1 0.2%
1996 708 644 64 32 9.0% 1 1 0.1%
1997 507 430 77 33 15.4% 4 3 0.8%
1998 295 257 38 13 13.6% 2 1 0.7%
1999 505 451 54 28 10.7% 1 0 0.2%
2000 421 336 85 40 20.4% 7 4 1.7%
2001 84 74 10 5 11.9% 2 2 2.4%
2002 68 63 5 2 7.4% 1 1 1.5%
2003 65 59 6 3 9.2% 2 2 3.0%
2004 191 161 30 17 15.7% 9 9 4.7%
2005 173 143 30 13 17.3% 8 8 4.6%
2006 172 138 34 15 19.8% 9 7 5.2%
2007 191 138 53 31 27.7% 29 27 15.2%
2008 25 18 7 4 28.0% 4 4 16.0%
2009 50 38 12 9 24.0% 9 7 18.0%
2010 126 81 45 34 35.7% 33 32 26.2%
2011 93 70 23 12 24.7% 13 11 14.0%
2012 98 86 12 4 12.2% 3 3 3.1%
1980-2012 8,082 7,294 788 375 9.7% 139 123 1.7%

46
Table 5
Analyst Coverage After the IPO
This table reports the percentage of small and large company IPOs during 1994–2009 with a
midpoint of the original filing range no lower than $8 that receive analyst coverage. 3,682 of the
4,075 IPOs during 1994–2009 satisfy the minimum midpoint requirement. Small and large
company IPOs are defined on the basis of whether the pre-IPO last twelve months sales exceeds
$50 million in 2009 dollars. Analyst coverage data are from I/B/E/S and other sources. “%
covered by a lead in year 1” reports the percentage of IPOs in cohort year t that has at least one
analyst report by a lead underwriter by the end of the first year after the issue date. “% covered
in year 1” reports the percentage of IPOs that have at least one analyst report from any source by
the end of the first year after the issue date. “% covered in year 2” reports the percentage of IPOs
that have at least one analyst report in I/B/E/S in the second year after the issue, conditional on
the IPO firm surviving into the second year. “% covered in year 3” is defined similarly as “%
covered in year 2”. To mitigate the concern that I/B/E/S analyst coverage data is incomplete, we
collect the I/B/E/S EPS forecast data on IPOs. If there is no recommendation but if an analyst
made an earnings forecast for a firm, we assume that the analyst also covered the firm.

47
IPO Year
Number of
IPOs
% covered by
a lead in year 1
% covered
in year 1
% covered
in year 2
% covered
in year 3
Mean no. of
leads per IPO
(1) (2) (3) (4) (5) (6)
Panel A: Small company IPOs (sales <$50m)
1994 132 84.8% 93.2% 83.3% 73.5% 1.0
1995 173 94.8% 96.5% 82.1% 68.2% 1.0
1996 316 97.8% 99.1% 96.2% 83.5% 1.0
1997 193 94.8% 97.9% 95.3% 81.3% 1.0
1998 118 99.2% 100.0% 88.1% 75.4% 1.0
1999 313 100.0% 100.0% 91.7% 75.1% 1.1
2000 263 98.9% 99.6% 90.9% 73.0% 1.1
2001 22 95.5% 95.5% 90.9% 77.3% 1.4
2002 12 100.0% 100.0% 100.0% 83.3% 1.8
2003 12 100.0% 100.0% 91.7% 91.7% 1.4
2004 60 100.0% 100.0% 100.0% 91.7% 1.5
2005 40 95.0% 100.0% 100.0% 97.5% 1.7
2006 42 95.2% 100.0% 100.0% 90.5% 1.5
2007 50 96.0% 100.0% 94.0% 88.0% 1.6
2008 4 75.0% 100.0% 100.0% 75.0% 1.5
2009 4 100.0% 100.0% 100.0% 100.0% 2.5
Panel B: Large company IPOs (sales > $50m)
1994 195 92.8% 99.5% 89.7% 73.8% 1.0
1995 211 93.4% 99.1% 89.6% 79.6% 1.0
1996 273 99.3% 100.0% 97.1% 85.7% 1.0
1997 216 100.0% 100.0% 97.7% 86.6% 1.0
1998 138 98.6% 100.0% 94.9% 81.2% 1.1
1999 144 97.9% 100.0% 93.1% 81.3% 1.2
2000 107 99.1% 100.0% 96.3% 87.9% 1.5
2001 55 98.2% 100.0% 98.2% 92.7% 1.6
2002 51 100.0% 100.0% 100.0% 92.2% 1.5
2003 48 97.9% 100.0% 95.8% 91.7% 1.6
2004 105 100.0% 100.0% 98.1% 96.2% 1.8
2005 114 98.2% 99.1% 94.7% 87.7% 1.9
2006 108 97.2% 100.0% 99.1% 89.8% 2.1
2007 105 97.1% 99.0% 98.1% 94.3% 2.0
2008 17 100.0% 100.0% 94.1% 94.1% 2.6
2009 37 100.0% 100.0% 100.0% 89.2% 3.0

48
Table 6
Quarterly Time Series Regressions of Scaled IPO Volume, 1975 to 2011
This table reports the results of maximum likelihood estimation of:
where the disturbance term, εt, follows a first-order autoregressive AR(1) process. The t-statistics
are reported in parentheses below the coefficients. Small and large firms are defined as firms
with, respectively, pre-IPO annual sales below or above $50 million ($2009). The dependent
variables are the number of IPOs (Model 1), the number of small firm IPOs (Model 2), and the
number of large firm IPOs (Model 3) in quarter t, all scaled by annualized quarterly real Gross
Domestic Product (GDP), measured in trillions of dollars ($2009). In Model 4, the dependent
variable is the fraction of IPOs that are from small firms. In 1977:Q3 and 1978:Q1, there were no
IPOs, and we set the fraction of small IPOs to the previous quarter value, 0.17 and 0.60
respectively. Time trend equals 0.01 for the first quarter of 1980 and increases by 0.01 for each
quarter onwards until the fourth quarter of 2011. SOX dummy is a post-Sarbanes-Oxley dummy
that equals one from the third quarter of 2002 to the fourth quarter of 2007, and zero otherwise.
Real GDP growth (%) in [t, t+3] is the percentage growth in real GDP from quarter t to quarter
t+3, downloaded from the U.S. Bureau of Economic Analysis. Future Nasdaq return in [t+1, t+4]
is the Nasdaq Composite Index return from quarter t+1 to t+4 (in decimals). Closed-end fund
discount (%) in t is the average monthly closed-end fund discount in quarter t, downloaded from
Jeffery Wurgler’s website (in percentages). Log M/B for small firms is the market-to-book ratio
for small firms (defined as less than $250 million in fiscal year sales using $2009), calculated as
the log of the sum of market value of small firms divided by the sum of book value of small
firms. Both the market value and the book value are measured at the end of quarter t-2, (i.e.,
three to six months prior to each IPO in quarter t). Nasdaq return in [t-2, t-1] is the Nasdaq
Composite Index 6-month return (in decimals) in quarters t-2 and t-1. IPO initial return in (t-1)
is the average first day return (in decimals) for IPOs in quarter t-1, defined as the difference
between the first day closing price and the offer price divided by the offer price. Percentage of
small public firms with negative EPS (%) in (t-1) is defined the same as in Table 2. Quarter 1
dummy is a first quarter dummy that equals one in the first quarter of each year, and zero
otherwise. The Durbin-Watson statistics and the pseudo R-squareds are also reported. The
estimation results are based on 148 quarterly observations from the first quarter of 1975 to the
last quarter of 2011.
1 2 3 , 3
4 1, 4 5 4
6 2 7 2, 1 8
IPOVolume Time trend SOXdummy Real GDP growth
Future Nasdaq return Closed-end fund discount
Log M/Bfor small firms Nasdaq return IPOinitial retu
t t t
t t t
t t t
α β β β
β β
β β β
+
+ + −
− − −
= + × + × + ×
+ × + ×
+ × + × + ×
( )
1
9 1 10
2
1
rn
Percentage of small public firms with negative EPS Quarter 1 dummy ,
, 0, ,
t
t t
t t t t
u u N
β β ε
ε ρ ε σ
−
−
−
+ × + × +
= × + :

49
Panel A: Quarterly time series analysis of IPO volume
Measures of the dependent variable, IPO volume
IPOs/Real
GDP
Small firm
IPOs/Real
GDP
Large firm
IPOs/Real
GDP
Small firm
IPOs/IPOs
(Model 1) (Model 2) (Model 3) (Model 4)
Time trend -7.51 -4.62 -3.12 -0.26
(-2.02) (-2.01) (-1.74) (-2.46)
SOX dummy -0.45 -0.40 0.01 -0.06
(-0.27) (-0.40) (0.01) (-0.98)
Real GDP growth (%) in [t, t+3] 0.47 0.24 0.22 0.01
(2.29) (2.01) (2.18) (1.29)
Future Nasdaq return in [t+1, t+4] -5.14 -3.13 -2.02 0.03
(-4.43) (-4.63) (-3.49) (0.61)
Closed-end fund discount (%) in (t-4) -0.17 -0.12 -0.05 -0.01
(-1.57) (-1.85) (-1.03) (-1.76)
Log M/B for small firms in (t-2) 3.33 1.96 1.32 0.24
(2.82) (2.82) (2.25) (5.01)
Nasdaq return in [t-2, t-1] 3.58 1.89 1.72 0.02
(2.47) (2.25) (2.36) (0.25)
IPO initial return in (t-1) -1.33 -1.53 0.07 0.08
(-0.56) (-1.10) (0.06) (0.69)
Percentage of small public firms 0.11 0.06 0.06 -0.00
with negative EPS in (t-1) (0.99) (0.94) (1.02) (-0.86)
Quarter 1 dummy -1.66 -0.69 -0.97 0.02
(-4.84) (-3.49) (-5.59) (1.08)
AR(1) coefficient, ρ 0.51 0.53 0.48 0.32
(6.78) (7.21) (6.35) (3.86)
Constant 3.69 2.23 1.34 0.49
(0.85) (0.86) (0.63) (3.02)
Pseudo R-squared 78.7% 78.7% 75.0% 64.5%
Durbin-Watson 2.08 2.00 2.19 2.00
Panel B: Means and standard deviations of scaled IPO volume
No. of
IPOs
No. of small
firm IPOs
No. of large
firm IPOs
Small firm
IPOs/IPOs
Mean 5.46 2.74 2.71 0.41
Standard deviation 5.16 3.01 2.38 0.20

50
Table 7
Long-run Returns on IPOs Categorized by the Pre-issue Sales of the Firm
IPOs from 1980-2009 meeting the Table 1 selection criteria are used, with buy-and-hold returns
calculated from the first CRSP-reported closing price through the earlier of the third year
anniversary of the IPO, the delisting date, or December 31, 2012. Buy-and-hold abnormal returns
(BHAR) are defined in equation (1) in the text. The sample size is 7,440 firms. Small and large
company IPOs are defined on the basis of whether the pre-IPO last twelve months sales are less
than or greater than $50 million (using 2009 purchasing power based on the CPI).
Market-adjusted returns use the CRSP value-weighted index returns. Style adjustments use firms
matched by market cap and book-to-market ratio with at least five years of CRSP listing and no
follow-on equity issues in the prior five years. For post-issue book values we use the post-issue
common equity numbers from the Thomson Reuters new issues database with corrections that
rely on the prospectus. For the remaining missing numbers we use the equity book values
reported for the nearest quarter after the IPO on COMPUSTAT, and further missing numbers are
calculated using the reported pre-IPO equity book values plus the amount of the proceeds
(assuming that overallotment option shares and costs of issuing offset each other) times the
fraction of primary shares in the IPO. If the post-issue book value is still missing (48 IPOs), we
use the market-adjusted return as the style-adjusted return. For IPOs with dual-class shares, the
denominator of the post-issue book-to-market ratio is calculated using the post-issue number of
shares for all share classes multiplied by the first closing market price of the publicly traded
share class. All returns include dividends and capital gains, including the index returns.

51
Number
of IPOs
Average
First-day
Return
Average 3-year Buy-and-hold Return
Sales Unadjusted Market-adjusted Style-adjusted
1980-1989
small
large
2,047
1,087
960
7.2%
9.1%
5.1%
22.6%
12.0%
34.6%
-22.5%
-34.4%
-9.2%
2.3%
-2.3%
7.7%
1990-1998
small
large
3,615
1,784
1,831
14.8%
18.5%
11.2%
39.8%
27.5%
51.8%
-20.9%
-34.9%
-7.4%
-0.5%
-7.6%
6.4%
1999-2000
small
large
2001-2009
small
large
858
603
255
920
273
647
64.4%
72.3%
45.7%
11.9%
8.6%
13.2%
-53.3%
-69.2%
-15.8%
15.7%
-10.0%
26.6%
-31.9%
-47.3%
4.7%
3.9%
-19.5%
13.7%
-58.9%
-67.0%
-39.9%
-6.0%
-30.3%
4.2%
1980-2009
small
large
7,440
3,747
3,693
18.1%
23.7%
12.4%
21.4%
4.8%
38.3%
-19.6%
-35.6%
-3.3%
-7.2%
-17.3%
3.1%

52
Figure 1. The number of U.S. IPOs by year, 1980-2012, with pre-IPO last twelve months sales less than (small firms) or greater than
(big firms) $50 million (2009 purchasing power). Table 1 lists the numbers that are graphed here.

53
0%
10%
20%
30%
40%
50%
60%
70%
Large firms
Without SOX costs
Small firms
Figure 2. This graph shows the percentage of seasoned publicly traded firms with negative earnings per share (EPS) each year,
categorized by small and large firms on the basis of an annual sales cutoff of $250 million (2009 purchasing power). We start from the
entire Compustat database, and select companies using the CRSP/Compustat linking table that have at least three years of records in
CRSP and Compustat. For example, for fiscal 2008, only stocks that have accounting data and stock prices for 2008 and that have
been publicly traded since 2005 are included. The solid line is for small companies and the dashed line is for large companies.
Beginning in 2002, for each firm we add SOX costs per share back and recalculate the percentage of firms that would have been
unprofitable without the SOX costs, and report these percentages as the dotted lines. Based upon the numbers in Table 9 of the
S.E.C.’s 2009 Office of Economic Analysis report, we add back $650,000 and $2,536,000 (2009 purchasing power) to the firm's
after-tax earnings for, respectively, small and large seasoned firms.

54
Figure 3. The percentage of exits via IPOs (top) and trade sales (bottom) of venture capital-backed portfolio companies in the U.S.,
1990-2012. Writeoffs are not included. Source: Tables 9.0 and 10.0 (pp. 13-14) of the National Venture Capital Association 2013
Yearbook.

55
0
3
6
9
12
15
0
9
18
27
36
45
S
c
a
l
e
d
q
u
a
r
t
e
r
l
y
v
o
l
u
m
e
S
h
i
l
l
e
r
P
E
Shiller
Big Firm
Small Firm
Figure 4: The Shiller P/E ratio is taken from Robert Shiller’s website and is computed as the ratio of the S&P 500 index divided by the
inflation-adjusted ten-year moving average of S&P 500 earnings. Scaled IPO volume is quarterly IPO volume divided by annual real
GDP, in trillions of 2009 dollars. Small and Big Firm IPOs are defined on the basis of $50 million in inflation-adjusted pre-IPO annual
sales. Panel B of Table 6 reports the means and standard deviations of the scaled small and big firm IPO volume. IPOs are operating
company IPOs.

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