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The Choice of Going Public and Going Private: Evidence from UK
Alon Brava, Omer Bravb, Wei Jiangc
a
Duke University, Durham, NC 27708, USA
b
c
Lehman Brothers, New York
Columbia University, New York, NY 10027
Abstract
Using a database of virtually all incorporated firms in the UK, public and private, we study the
transition of firms from a quoted to unquoted status and vice versa. We find that firms are more
likely to be quoted when they face large investment opportunities. Firms are more likely to be
quoted on a stock exchange when they are already engaged in high levels of capital investment,
when their industry market to book valuations are high and when their growth rates are high.
After going public firms’ investment intensity increases.
Keywords: Initial Public Offering, Going Private
1. Introduction
The decision to list on or delist from a stock exchange is one of the most important events in a
company’s life cycle and has generated a wide array of theoretical contributions in the corporate
finance literature. While many theories have been proposed to explain why some firms transit
from one status to the other and others do not, there is little empirical evidence in the area. This
state of affairs is not surprising, however. As argued by Ritter and Welch (2002), formal theories
of IPO activity are difficult to test since we usually only observe the set of firms that actually go
public and not those private firms that could have gone public but did not. Moreover, lack of
empirical evidence affects not only our ability to test theories of IPO activity but also the
transition from public to private status (as we do not observe what happens with the firms after
going private), and more generally the tradeoff between being and not being listed on a stock
exchange.
Using a new database containing information on virtually all firms in the U.K., public
and private, we are able to provide an extensive set of tests of models that make predictions
regarding the tradeoff between being listed on a stock exchange versus remaining private.
Our paper builds on earlier work by Pagano, Panetta and Zingales (1998) who focus on
the going public decision of a sample of Italian firms. Pagano et al find that larger companies and
companies in industries with high market to book ratios are more likely to go public, and that
companies going public seem to have reduced their costs of credit. Interestingly, they find that
capital expenditure and growth are only secondary factors that explain IPO activity while high
investment and growth do not follow after going public. This paper differs from Pagano et al. in
at least two major aspects. First, while the stock market plays an important role in the UK
economy (as in the US), it plays a much limited role in Italy. As a result, this study provides
direct evidence on the going public/private decisions for economies where the stock market plays
a significant role. Furthermore, Aganin and Volpin (2003) argue that:
“Recent contributions show that the Italian corporate governance regime exhibits low
legal protection for investors and poor legal enforcement (La Porta, et al., 1998),
underdeveloped equity markets (La Porta, et al., 1997), pyramidal groups, and very
high ownership concentration (Barca, et al., 1995). Arguably, due to these
institutional characteristics, private benefits of control are high (Zingales, 1994), and
minority shareholders are often expropriated (Bragantini, 1999).”
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Similarly, Zingales (1994) provides an example of how the Italian legal system provides
exceptionally weak protection of minority rights. These facts raise the concern that it may be
hard to extrapolate Pagano et al’s results from the Italian market to more developed financial
markets like the U.K. or the U.S.
Second, instead of treating the decision to go public as a one shot irreversible decision,
we view the decision to be public as a reversible dynamic decision (see Benninga, Helmantel and
Sarig (2003)). The approach taken in this paper builds on the idea that the tradeoffs that
determine whether are firm will be quoted should apply to private as well as public firms. If the
tradeoffs between being public or private are the same regardless of the state of the firm (up to
transaction costs which can be captured by controlling for the previous state of the firm), the
proper population of interest is all the firms, not only private firms, and the relevant model is one
that explains the state (public or private) of the firm rather than the decision to go public. This
approach, as clarified below, treats the whole path of each firm as one observation without
ignoring the information content in the decision made by the firm once it has gone public. Last,
the third benefit from our analysis is purely econometric and stems from the fact that studying a
much more active stock market like in the U.K., allow for a large number of transitions between
public and private status (and vice versa) and thus increased statistical power for our tests.
The rest of the paper is organized as follows. In Section II we provide a summary of the
theoretical literature regarding the decision to go public and private. Section III describes the
data. First we describe the data sources and their qualitative characteristics, and then the sample
under study. Section IV discusses the theoretical motivation for the empirical tests. Section V
contains the results of the paper. We conclude in Section VI.
2. Literature Review
Several reasons have been proposed in the academic literature to explain why owners of
firms decide to go public.1 In a survey of new stock market entrants, Roell (1996) documents
five reasons, among which three were reported by stock market entrants themselves. The first is
1
Throughout the paper we use the terms public, quoted and listed interchangeably. In all cases we mean a firm
whose shares are traded on a stock exchange. Notice, however, that in the UK “Public” refers to the legal status of
the firm while “Quoted” companies are those companies listed on a stock exchange. In other words, while private
firms in the UK are necessarily unquoted, public firms may be quoted or unquoted. See also section ??? for further
distinction between these two terms.
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access to new finance. The motives for new finance include prospects of growth by acquisition,
funds for organic expansion and refinancing of current borrowings. Yet, this in itself does not
justify an IPO since bank loans or private equity placements may equally well finance the need
for funds. Leland and Pyle (1977) and Chemmanur and Fulghieri (1999) argue that entrepreneurs
gain by going public because diversified investors value firm shares more than underdiversified
entrepreneurs. Black and Gilson (1998) argue that the assumption of private benefits of control is
a standard feature in venture capital models and, more generally, in models that seek to explain
the incentive properties of capital structure and that at least for entrepreneurs, appears to be
descriptively accurate. The failure rate for startup companies is high enough so that without a
large private value for control, many potential entrepreneurs would decide not to leave a secure
job to start a new company. By going public, the entrepreneur can raise money from many small
investors without loosing control. Moreover, Black and Gilson (1998) argue that in the case of
venture capital back companies, the IPO exit of the venture capitalists gives the entrepreneur the
opportunity to regain control over the firm. With the same spirit of taking into account the
private benefits of control, Pagano and Roell (1998) argue that by going public the initial owner
can raise money while achieving the optimal ownership structure from her point of view. This
optimal structure is not too concentrated in that it maximizes firm value net of monitoring costs,
because she takes into account her own future private benefits. Such sufficiently dispersed
ownership structure is in general less costly when the firm is public (depending on the fixed costs
of going public versus the variable costs associated with each additional shareholder when the
firm remains private).
A second reason for going public is enhanced company image and publicity (see
Stoughton, Wong, and Zechner (2001)). Public listing provides not only an initial certification by
financial market professionals but also a longer term price signal to suppliers, workforce and
customers. A robust equity price in the aftermarket reassures suppliers that they can safely grant
trade credit, to workers that they can expect a fairly stable job, and to customers that the product
will be supported after their purchase. As argued by Stoughton et al (2001) there is a critical
importance that consumers react to the information contained in the stock price and do not base
their purchase decision only on whether the firm went public. This fact insures that indeed a
separating equilibrium exists, and the high quality firms go public.
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The third reason for listing is to motivate management and employees. This is a natural
response to the company’s signal of growth, but more importantly, share participation schemes
help to retain and motivate senior management and employees. Presumably this cannot be
achieved with private equity, because employees do not wish to be at the mercy of the
controlling group when they leave the company and want to cash out their stake. Alternatively,
as suggested by Holmstrom and Tirole (1993), a well informed stock price is of value in itself as
an input into managerial performance-linked compensation, thus reducing agency costs.
Fourth, issuing the firm’s shares on a stock exchange is a means for the initial owners to
cash out. Obviously, as noted in Roell (1996), this reason is not emphasized in IPO prospectuses.
Nonetheless, Roell documents a few studies that report that a significant share of the money
raised from the public went to the original owners. Divestment by the initial owners does not
necessarily have to happen at the IPO, but rather tends to continue in the years following the IPO.
For example, Brennan and Franks (1997) find that in less than seven years after the IPO, almost
two thirds of the offerings company’s shares have been sold to outside shareholders. More
specifically they argue that “The pattern of ownership post-IPO is consistent with the view that
going public is a vehicle for the disposal of shares by non-directors”. Regarding venture capital
backed firms, Black and Gilson (1998) emphasize the importance of exit by the venture capital
fund from its investments. Clearly, cashing in cannot be a reason by itself to go public, as the
initial owners can sell the firm privately. Black and Gilson (1998) argue that exit (or cashing in)
of the venture capital through an IPO rather than through a private sale is optimal as it is a
method to return the private benefits of control to the entrepreneur. Zingales (1995) argues that
there are two possible sources of a buyer’s higher valuation which the incumbent should seek to
capture: the increase in cash flow and the increase in private benefits of control. In addition, the
market for cash flow rights is populated by a large number of small investors and so is fully
competitive, while the market for controlling blocks, which is restricted to a few large investors
who derive private benefits from controlling a company, is not fully competitive. If the potential
buyer is expected to increase the future value of cash flow rights, Zingales argues that while the
incumbent will not be able to extract the buyer’s full reservation value through direct bargaining,
by selling first the cash flow right to dispersed shareholders, the incumbent is able to fetch the
cash flow right’s full value under the buyer. Therefore, Zingales concludes that by selling the
company by first going public the initial owners facilitate the acquisition of their company for a
higher value than they would get from an outright sale.
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The fifth possible reason for going public is when initial owners identify mispricing in
the capital market. For example, in documenting the long run underperformance of IPOs, Ritter
(1991) argues that the patterns of the data are consistent with an IPO market in which investors
are periodically overoptimistic about earnings potential of young growth companies and firms
take advantage of these “windows of opportunity”. Similarly, Lerner (1994) shows that venture
capital backed companies go public when equity valuations are high and employ private
financings when values are lower.
There are at least two additional reasons for firms to go public. First, as suggested by
Amihud and Mendelson (1988), going public make the firm’s shares more liquid and so more
valuable to its owners. Second, Benveniste and Spindt (1989) and Maug (2000), among others,
argue that IPOs allow entrepreneurs to use share prices to infer investor valuations of their firm.
This information can be used in post-IPO investment decisions.
While the theories discussed focus on going public decision, there are several benefits to
remaining a private firm. First, the registration and underwriting costs of an IPO. For example,
Ritter (1987) reports that on average these costs amount to 14% of the funds raised. Second, the
advantage of staying private which allows the company to avoid ongoing administrative costs
associated with being public (e.g. filing requirements, audited financial statements, etc.). Third,
the well documented underpricing at the time of an IPO serves as another cost of going public.
For example, Loughran, Ritter and Rydqvist (1994) report an average initial return of 15.3% in
the U.S. Fourth, as suggested by Yosha (1995), among others, the increased disclosure of inside
information required from public firms serves as an additional cost. Such disclosure might
reduce the competitive advantages of the company. Finally, going public naturally creates a
separation between ownership and control. This separation may lead to agency problems (Jensen
and Meckling (1976)). For example, Jensen (1986) argues that many of the benefits in going
private and leveraged buyout transactions seem to be due to the control function of debt. Jensen
argues that desirable leverage buyout candidates are frequently firms or division of larger firms
that have stable business histories and substantial free cash flow – situation where agency costs
of free cash flow are likely to be high. Opler and Titman (1993) argue that several organizational
aspects of leveraged buy outs (“LBOs”) may allow firms to realize the gains while avoiding
many of the associated costs of financial distress. These features include (1) an institutionalized
debt workout process that may lower bankruptcy costs, (2) strip financing where debt and equity
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are owned by the same investors which decreases conflict between different classes of security
holders , and (3) LBO sponsorship by specialist firms with reputational incentives to look out for
debtholder interests.
3. Data
1.0. Sources
The data for this paper comes from several sources. We obtain balance sheet, income
statement and cash flow statement information from the Financial Analysis Made Easy (FAME)
database. Information on IPOs (going public) and public takeovers (going private) deals is taken
from the SDC Platinum (“SDC”) database, and is complemented with Zephyr for the period
1997 to 2003. Data for calculating industry market to book valuations is taken from the
Worldscope database. Finally, to compute industry R&D medians (classified by U.S. SIC codes)
we extract R&D values from Compustat for US public firms. Since the use of FAME is quite
novel, we provide some information on it below.
FAME is a database provided by Bureau van Dijk (“BvD”). BvD is one of Europe's
leading electronic publishers of business information.2 Under current company legislation in the
U.K. companies have a specific period of time from their year end date in which they must file
their accounts (Balance sheet, Profit & Loss and Cash Flow statements) at Companies House.
Companies House is an executive agency of U.K. Department of Trade and Industry. The main
functions of Companies House are to incorporate and dissolve limited companies, examine and
store company information delivered under the Companies Act and related legislation, and make
this information available to the public.3 The time period in which the company must file its
accounts at Companies House depends on the type of the company. A Public Limited Company
has up to 7 months and a Private Limited Company has up to 10 months from its year end date to
file its accounts.4 Once accounts are filed at Companies House they are processed and checked,
put onto microfiche, and made available to the public. Companies House aims for a turnaround
2
For more information about BvD: http://www.bvdep.com/.
For more information about Companies House: http://www.companieshouse.gov.uk/about/functionsHistory.shtml.
4
It is worthwhile to note here that “public” in the UK context refers to the legal status of the firm. Although being a
public firm is one necessary condition for being listed on the London Stock Exchange (LSE), being public does not
mean necessarily that the firm’s shares are traded on the stock exchange (for further details about requirements to be
listed on the LSE see section 2.0). In fact, most public firms in the UK are not quoted. For further details about the
definition and requirements from public firms in the UK see the Companies House website at:
http://www.companieshouse.gov.uk/about/gbhtml/gbf1.shtml#two.
3
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time of 7-14 days. Jordans, a U.K. leading provider of legal information,5 collects data from
Companies House daily and transfers it from microfiche to their database with a turnaround time
of 3-5 days. Finally, BvD collects data from Jordans on a weekly basis and creates the
appropriate search indexes to link with the search software. Once these indexes are tested, a
DVD-ROM is created and sent to a manufacturer for duplication and then issued to clients. The
DVD version used in this paper is the November 2003 release 173.0.6
There are two main categories of variables in FAME - static and annual. When a variable
is annual (mainly accounting data) the values of a given variable are reported for each
accounting year end. While FAME includes data for active and dead firms, it keeps data for no
more than 10 years for each firm. Hence, companies that have existed long enough and their last
year of reported data is before 2002 (mainly firms which have ceased to exist), may have
accounting data which dates back prior to 1993.
Similarly, the accounting data of active
companies dates back at most to 1993 if they have their accounts filed in FAME only up to 2002
and back to 1994 if they have their 2003 accounts already filed in FAME or, obviously, later if
they were incorporated after 1993. To avoid any selection bias we use in the analysis below only
sample years for which FAME includes all those firms which were registered at the time in
Companies House. Therefore the period of analysis in this paper is 1993-2003.7
When a FAME variable is static (or a header variable) this means that only the last year’s
reported value exists in the database. Unfortunately, some informative variables, such as the
company type (private, public unquoted, public quoted etc.), are static even though they may
change from time to time. This fact implies that the history of the firm related to its quoted status
needs to be extracted from other sources. We gather information from two sources to extract this
information. The first is SDC Platinum, a Thomson Financial database. SDC contains
information on multiple deal types including M&A activity, IPOs, going private and joint
ventures. Data for the U.K. is available in SDC for the whole sample period from 1993 to 2003.
We identify firms that listed on the London Stock Exchange (“LSE”) by extracting all the IPO
5
For more information about Jordans and links to other Jordans websites: http://www.jordans.co.uk/.
We thank Mitch Gouss from the New York branch of Bureau van Dijk for providing us with the FAME DVDROM
7
Since part of the active firms have already accounts for 2003 and some only to 2002, the period that truly contains
data on all firms in the UK is 1994-2002. However, in order to avoid the loss of data we define our sample period to
be 1993-2003.
6
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deals, and firms that delisted by extracting all going private deals. In addition, since SDC does
not cover all IPO and going private deals, we complement it with Zephyr. Zephyr, like FAME, is
a database provided by BvD. Just like SDC, Zephyr contains information on multiple deal types
including M&A activity, IPOs, public to private and joint ventures. There is no minimum deal
value for inclusion and senior researchers at Zephus verify all deals before adding them to
Zephyr. Data for the U.K. in Zephyr begins in 1997. For the period 1997 to 2003 Zephyr gives a
more complete coverage of the IPO and going private deals. Indeed, the two sources do not
overlap for the 1997-2003 period, but rather complement each other.
2.0. Sample
Since our goal is to study the determinants of the decision to list on or delist from the
LSE, we restrict attention to quoted and unquoted firms that satisfy the listing requirements for
the LSE. The main requirement that effectively restricts a firm from listing on the LSE is related
to the firm’s market value.8,9 A company that lists its shares on the LSE must have a total market
capitalization of no less than £700,000.10 The problem with this requirement is that the market
capitalization is unobservable for unquoted firms. Therefore, in the analysis below we consider
firms to satisfy the market capitalization requirement if according to the Companies House
definition they are “medium” or “large”.11
Since financial firms such as banks and insurance companies are intrinsically different in
the nature of their operations and accounting information, we exclude any firm that is classified
as financial according to its primary U.S. SIC code, primary US SIC code first digit is 6, from
FAME and the deals databases (SDC and Zephyr).
Since the definition of a firm’s status (public or private) and its transition status is crucial
to the analysis in this paper, it is worthwhile to clarify how this classification is done. Consider
8
Here we mean a requirement that cannot be overcome by management exerting some effort or cost.
For a detailed description of the listing requirements to the LSE see chapter 3, “conditions for listing”, in the
UKLA source book. This can be accessed at: http://www.fsa.gov.uk/pubs/ukla/chapt03-3.pdf. For a brief overview
see, “A practical Guide to Listing” from the LSE website, which can be accessed at:
http://www.londonstockexchange.com/livecmsattach/1222.pdf
10
This market cap requirement was taken from the 2002 sourcebook. I tried to contact both the LSE and the UKLA
to get older versions and see whether this requirement was intact during all my sample period. Both authorities said
they do not keep archives of the sourcebooks, and the only information I was able to get from somebody who works
in the UKLA for a long time is that “this requirement is there for quite a while”. Therefore, in this paper, I assume
that this market cap requirement was valid throughout the sample period (1993-2003).
11
I use also alternative selection procedure, described in detail in section 1.0, which provides very similar results.
9
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first the definition of a private to public transition. In reality, firm’s shares may become publicly
listed directly through an IPO, but it may also indirectly go public through a merger or
acquisition deal with an already publicly listed company. Since it is plausible that many of the
M&A deals are motivated by other economic considerations which are unrelated to the public /
private tradeoff - such as operating synergies, market monopoly considerations or tax advantages
- we define as a private to public transition only IPOs. Similarly, a firm may be delisted because
it went private directly or after being acquired by another unlisted firm. For similar reasons, we
include only going private deals (and exclude M&A deals) in the definition of public to private
transition.12 Hence, firms that appear in the deals databases at least once are defined as public
after an IPO and private before the IPO and vice versa for a public to private transitions. The
status of firms that are not involved in any transition (appear in neither SDC nor Zephyr) is
defined according to their “Company type” value in FAME.
Another issue arises in identifying when a company can be considered as publicly traded.
Besides the Official List (OL) and the Alternative Investment Market (AIM) on the London
Stock Exchange, by far the most important one, U.K. companies may list in at least another
important domestic exchange, the London OFEX, as well as internationally. In the results
presented below we include all available deals – firms that went public on any exchange are
treated as quoted after the IPO.13 Similarly, for non-deal firms, we classify as ‘quoted’ firms
whose company type is defined in FAME as equal to “Public Quoted”, “Public AIM” and
“Public OFEX”.14
12
In Zephyr a Public to Private deal is defined as one involving a public takeover which is financed by a venture
capital (this includes the various types of the commonly accepted going private deals: MBI, MBO, IBO and LBO).
In SDC, public to private deals are defined according to the “going private flag”.
13
Among the IPOs there were also 264 with missing stock exchange name.
14
“OFEX is a market for dealing in unquoted and unlisted securities. It is a market regulated by the FSA (Financial
Services Authority) but it is not a Regulated Investment Exchange nor is it a member of the Stock Exchange.
Companies on OFEX tend to be smaller than those that apply for membership to AIM, typically seeking to raise
capital in the region of £250,000 to £500,000. It also suits those companies not seeking to raise capital but who want
to create a dealing facility for their shareholders without having the burden and expense of meeting the main
exchange regulations. The requirements of joining OFEX are less onerous than those of applying to the Official List
or AIM.” (Source: http://www.grant-thornton.co.uk/pages/services-raising_finance_and_flotations-ofex.html). The
firms listed in OFEX and internationally represent a minority of the listings in my sample (85 and 9 IPOs
respectively, less than 10% of all the IPOs) and therefore should not have a significant effect on the results presented
in this version of the paper, one may be concerned that due to their different characteristic, these firms should not be
treated as publicly listed firms. Furthermore, the listing requirements we apply throughout, apply only on the LSE.
Therefore, as discussed in section Error! Reference source not found., for robustness check we plan to check the
results considering only listings on the LSE.
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3.0. Summary Statistics
It is important to note first, that all the figures in the tables are after dropping top and
bottom 1 percent of extreme values for each variable. Since apriori it is plausible to assume that
the distributions for quoted, unquoted, go private and go public firms are different, I drop (mark
as missing) extreme values separately for each of these 4 groups.
Table 1 contains summary statistics on the sample of interest – All quoted firms (as all of
these firms can elect to go private), and only private firms that are medium or large according to
the Companies House definition, which as discussed earlier serves as a proxy for the market
requirement for listing on the LSE. Notice that panel A is biased upwards relatively to panel B
since panel A includes only large and medium private firms as defined by the Companies House
while panel B includes all listed firms, regardless of their book size. For example, the minimum
total assets are 1401 and 49, respectively. To make sure that our results are not affected by the
fact that the analysis is tilted to low multiple industries, we repeat the analysis with market
capitalization approximated with industry multiples. Each panel includes all firm-year
observations that belong to the panel classification. Note that any single firm could belong at
different periods to a different panel. At the top of each panel is the number of firms that
belonged to the panel at least for one accounting period. As one may expect quoted firms are on
average larger in any dimension (Total assets, turnover, profit, CAPEX, Cash), however, some of
the unquoted firms are very large and are comparable to the large quoted firms.
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Table 2 presents the sample summary statistics. It provides information on the subset of
firms that were involved in a transition from public to private or vice versa. Since the sample
period is 1993-2003, and since the analyses below require data on the firm before the deal took
place, the information collected on the deals is for the period 1994-2003.15 Panel A provides
summary statistics of the IPO deals immediately before and after the IPO. Since some 40% of
the IPO deals did not have a record in the FAME database before the IPO as the firm was
incorporated just before as a holding group, we collect the data for these firms manually from
their IPO prospectuses. A few distinct features of the data that will be further explored in Section
V can be already seen. Not only do IPO firms grow larger, as might be expected due to the
raising of new capital, their capital expenditure increases and their leverage decreases
significantly. More importantly, comparing the summary statistics of the IPO firms with those of
the universe of the unquoted firms that satisfy the listing requirement (panel B of table 1), firms
that choose to go public have a higher level of capital expenditures (before and after the IPO)
and a much higher growth rate.
Panel B provides some summary statistics of the going private deals immediately before
and after the deal. First notice that the growth rate and level of capital expenditures decrease
after going private. In addition also profitability decreases. Comparing firms that go private to
the universe of quoted firms (panel B of table 1), the average quoted firms that choose to go
private is smaller but the median is larger.
4. Factors related to the quoted/unquoted Status of the firm
In examining the public versus private tradeoff, we focus on certain firm and industry
level characteristics that are observable and apriori may influence the relative attractiveness of
one status over the other (Brau, Francis and Kohers (2003)). We discuss the possible impact of
these factors in the following subsections. It is important to point out that some of the theories
presented in the literature review section do not have empirical testable implications. More
importantly, since firms are not homogenous, and different firms may be motivated to go public
15
The numbers of deals are comparable to those presented in other papers. For example, for the period from1998 to
2000, Weir and Laing (2000) find 116 public to private transactions including financial firms, and 95 transactions
excluding financial firms and firms with missing data. In our sample there are 118 public to private transactions of
non financial firms for the same period. Khurshed et al (2004) report 415 initial public offerings of U.K. operating
companies for the period 1995 to 1999 on the LSE market only. Our sample for the same period consists of 488
IPOs, of which 14 were on OFEX, 6 on international exchanges and 153 with a missing stock exchange name.
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or private for a combination of different reasons with different weights, an estimated coefficient
that is not consistent with the predictions of a theory cannot provide enough evidence to reject
the theory. In other words, the purpose of the analysis in this paper is not to distinguish among
or reject any of the theories as possible explanations to the going private and public activity, but
rather, loosely speaking,
to see “on average” which of the theories play a major role in
explaining the public to private and private to public transitions.
1.0. Previous Status of the firm
The transition between being quoted and unquoted on a stock exchange is not costless.
As noted in the introduction the registration and underwriting costs of an IPO are substantial.
There are also substantial frictions in going private that are highlighted in Meisner (2002) and
Johnson and Weidhaas (2001). Most going-private deals are done by large equity funds that
specialize in leveraged buyouts. Most of these investors generally look at going-private deals as
a costly and time consuming since “they still have to find a buyer for it or take it public again so
they can see a return on their investment, and that's a real pain.” A second factor is the sheer
legal complexity involved. “Neal Suggs, a securities lawyer with Orrick Herrington & Sutcliffe
LLP in Seattle, argued that going-private deals are much more complicated than initial public
offerings.” A third factor that might constrain going private transaction is that at times in which
debt markets tighten, financing such deals necessarily becomes costlier. Fourth, going private
transactions take a long time to complete. It is difficult for buy-out firms to commit to a process
that may take six months to complete, if it is completed at all. Therefore, “everything else equal”,
the probability of a quoted (unquoted) firm to be quoted (unquoted) in the following period
should be larger than that of an unquoted (quoted) company. In addition the previous status may
proxy for unobserved time invariant effect (such as firm desire to have a specific type of
corporate governance and therefore choose to stay private every period). This would have the
same effect as the frictions discussed above.
2.0. Size
Several theories predict that the propensity to go public should be higher for larger firms.
On the cost side of going public, a larger firm may be less exposed to the adverse selection costs
due to informational asymmetries between the issuer and the less informed investors at the time
of the IPO. The adverse selection cost may be a more serious obstacle to the listing of small
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companies (controlling for age) which have little track record and low visibility than larger
companies.
In addition, while many of the ongoing administrative expenses of publicly listed
companies are fixed (Pagano et al (1998) and Ritter (1987)) some of the benefits are positively
related to the size of the company. First, if larger companies are involved in larger investment
projects, then being quoted would play a more important role for such companies in overcoming
borrowing constraints and gaining access to an alternative source of finance. An obvious
objection to this argument is that holding constant the level of a company’s capital expenditure,
the size effect should be eliminated. However, this objection is invalid if at least some of these
firms start their actual investments only after raising the capital in the public markets. Second, as
suggested by Amihud and Mendelson (1988), going public make the firm’s shares more liquid
and therefore more valuable to its owners. Since the liquidity of a company’s shares is increasing
in its trading volume, this advantage is more relevant to larger firms. We use two measures of
firm size in the analysis: total assets and turnover.
3.0. Age
The age of the firm may be related to the propensity of private firms to go public in two
different ways. On the one hand if the adverse selection cost in the IPO is more serious to the
listing of young companies, we would expect that older firms will be more likely to go public.
On the other hand, Pagano et al (1998) argue that practitioners talk about entrepreneurs’ “cultural
resistance” to take their companies public and we expect that old and unquoted firms are more
likely to be subject to this cultural effect. Since the cultural effect is unobservable and therefore
cannot be controlled for in the regression analysis, if this cultural effect is indeed playing a role,
we expect that the probability of unquoted firms to go public in the following period decreases
with the age of the firm.
4.0. Capital Expenditure
Raising capital to finance positive NPV projects is the most cited reason for listing the
shares of a firm on a stock exchange, and is a common assumption maintained by many
theoretical models in the academic literature. If this is indeed the reason for firms to go public,
and if firms start raising capital in other forms and engage in large scale investments before they
go public, we would expect to see that the higher the CAPEX (capital expenditure over property
-13-
plant and equipment) the higher the probability a firm will be quoted the following period. In
addition, we expect that after going public the CAPEX will increase or at least not decrease.
Note that the measure investment is imperfect. Firms with projects that are human capital
intensive will not show these expenditures in the CAPEX cash flow item but rather under R&D
item in the Profit and Loss (“P&L”) account and as a sub item of the cash flow from operating
activity in the cash flow statement. Unfortunately, the P&L accounts in FAME are not detailed
enough and the R&D item is not available. Therefore, while CAPEX is a reasonable proxy for
investment intensity in asset intensive industries, for human intensive industries, such as some
parts of the high tech industry, CAPEX may underestimate investment intensity. We try to proxy
for R&D expenses with the difference between gross and operating expenses, but as will be
discussed later this is probably not a good proxy.
5.0. Growth
If the growth rate of the firm is a proxy for its future investment opportunities then, just
like CAPEX, we expect that firms with high growth rate will tend to go public, and quoted firms
with low growth rates will go private. We measure growth rate as the rate of growth in sales.
6.0. Industry Multiples
Industry multiples may be positively correlated with the probability of a firm to be quoted
for two reasons. The first is related to the theory that motivates the use of growth and CAPEX. If
investors are rational we would expect to see high valuations, and therefore high multiples, in
industries with large future growth opportunities. If these growth opportunities require large
investments, high industry multiples will be associated with a higher probability of going public.
As mentioned in the introduction, Ritter (1991) argues that the empirical evidence is
consistent with an IPO market in which investors are periodically overoptimistic about earnings
potential of young growth companies and firms take advantage of these “windows of
opportunity”. Similarly, Lerner (1994) shows that venture capital back companies go public
when equity valuations are high and employ private financings when values are lower. If this is
the case, private firms may choose to go public when they observe multiples that are
unjustifiably high for publicly listed companies in their industry. Similarly, if private equity
firms and management teams can take a firm private cheaply, we would expect that firms will go
private when the industry multiples are low. In other words, regardless of the current firm status,
-14-
the higher are the industry multiples, the higher is the probability the firm will be quoted the
following period. We measure the industry multiples as the median market to book value of
equity of all publicly listed companies on the LSE in the same industry.
7.0. Leverage
Leverage plays a role in the going public decision for two different reasons. First, if firms
go public because they face positive NPV projects and therefore engage in high levels of
investment financed initially by debt, we would expect that leverage will be positively correlated
with the probability of unquoted firms to go public. In addition, these firms might use the capital
raised in the IPO not only to further finance their projects but also to rebalance their capital
structure, hence, leverage is expected to decrease after going public.
Second, debt serves as a control mechanism to alleviate the agency costs of free cash
flow (Jensen (1986)). If this theory plays a major role in explaining the public/private status of
firms then the probability of quoted firms to go private should be negatively related to their
leverage.
8.0. Cash and Equivalents
Following the motivation of the agency theory in Jensen and Meckling (1976), and more
in particular, Jensen (1986), when firms have high levels of free cash flow with low level of
investment opportunities, management’s incentives may not align with those of its owners when
these two are separate – which is the case for publicly listed firms. In such a scenario payouts to
shareholders may be much lower than optimal. Management may be inclined to invest the free
cash in projects at below the cost of capital or waste it on organization inefficiencies. If this
theory plays a major role in explaining the transition of firms from public to private status we
would expect to see that higher level of cash and equivalents is associated with a larger
probability of the firm to be unlisted the following period. In addition we should expect to see a
decrease in the cash levels after going private.
9.0. Return on Assets
If high ROA is due to some proprietary knowledge, higher ROA firms have less incentive
to go public. In addition, Pagano et al (1998) suggest that ROA may affect the probability of
firms to be quoted in two more ways. On the one hand, Pagano et al argue that a more profitable
-15-
company would not be highly dependent on external equity, suggesting a negative impact of
profitability on the probability of an IPO. On the other hand, a company experiencing a
temporary surge in profits may list, hoping that investors will mistakenly perceive its high
profitability as permanent and will over value its shares (Ritter (1991)). In this case, we expect
profitability to be positively associated with the probability of going public.
Additional predictions are related to the ex post effect of a transition on profitability.
Firms with surplus may go public to increase firm’s performance by increasing employee moral,
tying management compensation to performance (Holmstrom and Tirole (1993)), and use market
information to make better informed investment decisions (Maug (2000)). If this is the case,
ROA should increase after going public. On the other hand if firms go private because of agency
problems (Jensen and Meckling (1976)), then after going private and restructuring the firm, ROA
should increase.
5. Results
The predictions outlined in the previous section are of two types: predictions on the
variables that should affect the likelihood of a transition ex ante and predictions on the likely
consequences of a transition, ex post. Therefore, to provide as much insight about the
public/private tradeoff, in the first subsection we perform the ex ante analysis, and in the second,
the ex post analysis.
Before presenting the results it is worthwhile to clarify the time notation (the ‘t’ subscript)
which is used throughout this section. For flow variables (e.g. CAPEX, turnover) the subscript t
denotes a variable measured over the period from accounting statement at time t-1 to accounting
statement at time t. For non-flow variables (e.g. Total assets, cash) t is simply the point at which
the variable is measured. The status variable, Quotedt+1, which is the dependent variable in all the
ex ante regressions, is equal to 1 if the company is quoted on a stock exchange at the accounting
statement date t+1, and 0 otherwise. All the independent variables in the regressions are
measured at time t. Finally, the time periods, in general, represent 12 months as the accounts are
annual. However, in some cases firms may change their accounting year cycle so the time that
elapses between two accounting statements may be more or less than 12 months. In such cases
we first annualize all the flow variables.
-16-
1.0. The determinants of public to private and private to public transitions
We model the ex ante predictions using a Probit setup and report the results in
table 3. The regression includes any firm-year observation of a public firm and of a
private firm that under the Companies House classification is considered to be medium or large.
In addition, to the lagged dependent variable (Quotedt), all of the explanatory variables are once
interacted with the Quoted dummy variable and once with the unquoted dummy variable.
Our main result is easy to summarize: firms with large current investment (CAPEX),
large future investments (proxied by the industry market to book) and large growth rates are
those who are more likely to go (or remain) public. This pattern is very strong for private firms
(all of these three variables are significant at the 1% level), and while weaker, applies also to
quoted firms. For quoted firms, the CAPEX is significant at the 5% level, and the growth is only
weakly significant.
As mentioned in the previous section, a significant coefficient on the market to book ratio
may also be due to the “windows of opportunity” hypothesis. Pagano et al (1998) propose a nice
way to discriminate between these two hypotheses (that is, to see if one or both of the theories
plays a role in explaining the pattern of the data) by relying on ex post evidence: if newly listed
companies invest at an abnormal rate and earn large profits, then the relationship between market
to book and the status of the firm is likely to be driven by expectations of future growth
opportunities; otherwise, it is likely to reflect the desire to exploit a window of opportunity. As
we show in the next subsection, IPO firms continue to invest at an abnormal rate and the
profitability of the subset of firms with high deficit weakly increases. This evidence implies that
firms go public to raise capital and overcome borrowing constraints but it does not help us to
discriminate against the windows of opportunity story which might play a role in conjunction
with the financing investment motive. To further identify whether the windows of opportunity
theory is present in the data, Pagano et al (1998) suggest an additional test based on ex ante
evidence: if raising funds for future investments is the main reason to go public, the likelihood of
carve outs should not be correlated with the parent firm’s market to book ratio, since in that case
the parent company already has access to the stock market. Unfortunately, reviewing over a 100
randomly selected IPO prospectuses we could not identify any carve outs in our sample. Notice
however that in the ex post analysis below the profitability as measured by EBIT (ROA) is not
-17-
affected (slightly decreases) after going public. For the subset of firms with low deficit it even
decreases. While this is consistent with the windows of opportunity story and not with the access
to capital market in face of positive NPV project motive, the profitability as measured by ROA
may not be affected or even decrease after going public for other reasons to be discussed below.
Profitability can serve at best only as an indirect test of the market timing hypothesis.
The next most statistically and economically significant result is that the transitions from
one status to another are extremely costly. The lagged dependent variable has t-statistics of at
least 15. The lagged status of the firm has such a high predictive ability for the future status of
the firm that the pseudo R square of the regressions is approximately 90% (without the lagged
dependent variable the pseudo R squares fall to the range of 13%). The extremely strong effect
of the lagged dependent variable implies that firms’ status in many cases may not be optimal but
rather influenced by historical reasons. A private firm may find it optimal to stay private, while
an otherwise identical firm from any operational aspect may find it optimal to stay public just
because it is already public. Stated differently; in a world without frictions discussed in previous
section, maximizing shareholders value would induce a much higher transition rate from one
status to the other. Another possible interpretation is that the lagged status is capturing some
latent time invariant variable as discussed in the previous section.
The results for cash and leverage do not lend support to the agency costs of free cash flow theory
in Jensen (1986). Leverage does not seem to be a factor driving the probability of being listed.
As for cash, firms with more cash are more likely to be quoted the following period. The source
of the positive effect of cash in
table 3 on the probability of being quoted is not clear.
The return on assets is insignificant throughout. This result does not provide evidence to
support the predictions in Pagano et al (1998), nor does it support the idea that ROA is a proxy
for proprietary knowledge of private firms that constrains them from going public.
The regression results indicate that the factors that determine the probability of being
listed when the firm is already listed are similar as when it is not yet listed (private). This result
is consistent with the approach taken in Benninga et al (2003). However, there are two
exceptions – the effect of age and size. Firm age is highly statistically negative in all regressions
-18-
for the private firms only. This result provides evidence against the role of the adverse selection
hypothesis in explaining why firms go (or do not go) public. As discussed in the previous section,
this result is consistent with the notion of a “cultural resistance” of many entrepreneurs to take
their companies public. Since this cultural resistance is not relevant to firms that are already
public, we do not see a similar effect of age for firms already listed.
Similar to the effect of firm age we find that the effect of size depends on the present
status of the firm. While larger private firms are more likely to go public, larger public firms are
more likely to go private. The fact that log size works in the opposite direction for private and
public firms is consistent with Meisner (2002) who argues that “…anything below $25 million is
a waste of time to the Warburgs of the world…” (Warburg is a large equity funds that specialize
in leveraged buyouts). The high frictions and fixed costs involved in the transition from one
status to the other overcome the benefits of a transition for small firms.
As noted earlier the fact that we do not observe market valuations of private firms creates a
potential bias in the way we select private firms in the ex ante analysis – after all, only those firm
that satisfied the LSE listing requirements could have entertained the option to go public. Hence,
in addition to the selecting private firms according to their size, as defined by the Companies
House, we employ an additional, multiples-based valuation approach as in Berger and Ofek
(1995). We construct proxies for the valuation of private firms in the sample and then use them
to decide whether any given firm, at any given month, satisfies the market capitalization
requirement.16 Specifically, using the Worldscope database, we first compute the market to book
equity ratio for every listed firm on the LSE, in every month.17 Next, for every month in the
sample we classify firms according to their two digit primary U.S. SIC code. For each monthindustry we compute a market to book multiple as the median multiple across the firms in each
industry classification.18 Finally, the estimated value of each firm in every month is the book
equity value of the firm multiplied by the market to book multiple of the industry it belongs to
16
For a thorough study valuing IPOs using multiples see Kim and Ritter (1999).
Note that while the market values used to compute these multiples are indeed monthly, the book values used are
from the annual accounting statements.
18
For a significant number of two digit SIC codes the number of firms used to calculate market to book multiples
are small. In order to ensure that these multiples are not affected by temporary shocks to the valuation of some of the
quoted companies, we compute the industry multiple in each month as a trailing average of the past six months.
17
-19-
(again defined according to its two digit primary US SIC code). The results applying this
selection procedure provide results that are qualitatively the same as to those presented in
table 3.
Table 4 presents the Probit regression results for the decision to go public with the
distinction between high and low R&D industries. Using data on R&D for public firms in the
U.S. from Compustat (item Data46) we classify different industries (classified according to US
SIC codes) to high and low intensity R&D industries. As discussed in the previous section, the
idea here is that if the difference between gross and operating profit plus depreciation is a good
proxy for R&D expenses, we would expect that in high intensity R&D industries this proxy will
be an important determinant for the same reason that the CAPEX is, and in low R&D industries
this proxy will have no (or lower) effect. As can be seen from in table 4 in both cases this proxy
is significant. As we will see in the next section, the ex post behavior of these two types of
industries is also very similar (that is, this proxy increases after going public). It therefore seems
that this variable is not a good proxy of R&D expenses, and the fact that it is significant is simply
because firms that go public are engaged in higher total SG&A expenses, which also increase
after going public.
2.0. The consequences of going private and public transitions
In comparison to the ex ante analysis in the previous sub-section, studying the ex-post
effect of going private and going public transitions is more challenging. One natural approach, in
the spirit of the ex post regressions in Pagano et al (1998), is to perform reduced form
regressions where the dependent variable is the variable that theory suggest to be affected by the
transition, and the independent variable is a dummy equal to 1 if the firm transitioned and 0
otherwise. The problem with these regressions is that the dependent variable is affected by many
factors that cannot be controlled for. Indeed, when we try to perform such regressions in various
forms, the R squared of these regressions is negligible. Trying to perform richer reduced form
regressions does not help much to increase the explanatory power of these regressions. Moreover,
the estimated coefficients (and specifically, the coefficient of interest on the transition dummy)
are extremely sensitive to the specific reduced form models. The problem with these richer
reduced form models is not only that they still do not capture all the factors that may affect the
accounting outcomes of the firm, but that such regressions suffer from a severe endogeneity
-20-
problem. For example, leverage is determined simultaneously with all the other outcomes of the
firm. A variant of this approach, taken in Pagano et al (1998), is to control for other aspects of
the firm with a fixed effects regression model. First note that these regressions did not increase
the explanatory power of the regressions to any meaningful level. More importantly these
regressions suffer from two serious problems. First a fixed effect dummy does not control for
time varying attributes of the firm. Second, a fixed effect estimator (or a difference effect
estimator for that matter) is consistent only when the independent variables are strictly
exogenous. If the decision to go public is affected by past outcomes of the dependent variable
this condition is clearly not satisfied. For example, If the level of CAPEX at time t affects the
decision to be public at time t+1, a fixed effects regression of CAPEX at time t+1 on a transition
dummy in period t will provide inconsistent estimates as the IPO dummy is not exogenous to
both future and past outcomes of the CAPEX. Furthermore, adding a lagged dependent variable
as an explanatory variable (which apriori seems to be an important control) produces inconsistent
estimates for the same reason, because the lagged dependent variable cannot be by definition
strictly exogenous.
Since we do not attempt to predict or explain the behavior of the various accounting
variables of the firm, a task which is beyond the scope of this paper, but rather to see only the
behavior of several characteristics of the firm before and after a transition, the approach taken in
this subsection is to perform a simple univariate analysis. In table 5 (table 6)we compare the
means in the period just before the transition with the means 1, 2 and 3 periods after for several
interesting variables of firms that went public (private).
The results of the ex-post analysis are consistent with the ex ante analysis from the
previous sub-section. First, for IPOs, in panel A (all IPOs) we can see that while firms use part of
the raised capital to rebalance their leverage, not only do they continue to have higher level of
investment (CAPEX) compared to their non IPO peers, but also they raise their investment level.
Second, cash levels increase which is a simple result of the infusion of cash from the going
public transaction. Third, absolute profitability (EBIT) is not affected, while ROA, if anything,
declines. From panels B and C it can be seen that this is driven mainly by IPO firms that have a
cash surplus and do not go public to raise capital but rather to cash in. This means that while
there is no fundamental change in the operations of the firm – hence their levels of profits remain
-21-
unchanged, because of the cash infusion of the going public transaction, the assets base increase
which decreases in the medium and short run profitability in ROA terms.
Looking more carefully at the behavior of cash constrained (high deficit) and cash
surplus firms in panel B and C, we can see that there is little evidence to support the idea that the
going public decision is motivated by the reasons suggested in Holmstrom and Tirole (1993) and
Maug (2000) – the profitability of firms that have cash surpluses (low deficit) does not increase,
and, if anything, it actually decreases. For this subset of firms that probably did not go public to
access the capital markets (as they have no shortage of capital) these models suggest that the
decision to go public was made to increase moral and productivity of employees and to improve
investment decision of management using the information embedded in the stock price of the
company. Taken together with the fact that larger firms go public, which supports the notion that
going public is more valuable due to liquidity reasons suggested in Amihud and Mendelson
(1988), the potential control motivations in Black and Gilson (1998) and Pagano and Roell
(1998)19, and diversification value of going public as in Leland and Pyle (1977), the results in
these two panels provide strong evidence that many IPOs (specifically -- low deficit firms) are
motivated by the desire of the incumbent (whether the entrepreneur or venture capital) to cash
out in an optimal (value maximizing) way. Comparing high and low R&D industries in panels D
and E the only conclusion that can be drawn is that our proxy for R&D expense is probably not
good, as we can see this proxy behaves very similarly (increases) in both subsets.
As for going private firms, their investment level does not decrease significantly. This
result does not provide evidence that going private deals are motivated by the agency problems
of Jensen and Meckling (1977) to prevent the management from investing in projects at below
the cost of capital. While the cash level decreases, the leverage does not seem to be affected on
average by the going private deals (if anything it decreases). This casts doubt as to how the
agency costs of free cash flow of Jensen (1986) are important in explaining the decision of taking
firms private. While the profitability, measured by EBIT and ROA decreases, this is a one period
decrease which probably is caused by the temporary costs involved in the transition.
19
Unfortunately we do not have annual data at this stage on the insider ownership to test these theories.
-22-
6. Summary of results
In this paper we employ a novel dataset containing all .... our goal is to test....
The main conclusion of this paper is that contrary to the results of Pagano et al (1998) for
the Italian market, the main reason firms choose to be public is to raise capital in the public
markets in the face of positive NPV projects. The results are also consistent with the windows of
opportunity (or market timing) story of Ritter (1991) but more direct tests of this theory is not
available with the data used in this study.
Second, the results related to the profitability variables (EBIT and ROA) do not lend
support to the motives of going public in the models of Tirole (1993) and Maug (2000). While
the related evidence here is indirect, the fact that profitability after going IPO does not increase
(if anything it decreases) in the whole sample of IPOs and, in particular, in the subset of IPOs
that are cash unconstrained, casts doubt as to whether these theories are important in explaining
transitions from one status to the other.
Third, the results related to the behavior of profitability after going IPO, and the effect of
size on the decision to become listed, suggest that going public is simply the optimal way for the
incumbents (whether by the entrepreneur or the venture capitalist) to cash out. This result is also
consistent with the liquidity value motive of being public as suggested in Amihud and
Mendelson (1988). Unfortunately, more direct tests of the cashing out and control stories were
not executed in this paper due to lack of relevant information about insider ownership.
Fourth, we do not find that the agency stories in Jensen and Meckling (1976) and Jensen
(1986) can explain the transition of public firms back to an unlisted status. Leverage does not
increase after going private, and investment intensity does not decrease as well.
Fifth, we do not find that adverse selection costs are a major factor in the decision to go
public.
Sixth, not surprisingly, the current status of the firm is a major factor in the determination
of the status of the firm in the following period. This variable is in fact the most statistically
significant factor. This result provides evidence in support of the idea that the decision to go
public or private is affected very much by the fixed costs that are involved in such a transition.
Finally, the data supports the approach taken in Benninga, Helmantel and Sarig (2003). While
-23-
quantitavely the effect of the variables on the decision to list or delist are different for private and
public firms, with the exception of the age and size they are qualitatively roughly the same. The
economic tradeoffs of listing a firm on the stock exchange are very similar regardless of the
present status of the firm. The qualitative difference in the result for age suggests that the
“cultural resistance” applies (not surprisingly) only to private firms. The qualitative difference in
the results for size is probably due to the high frictions involved in the transition from one status
to the other.
-24-
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Table 1
Entire Sample Summary statistics
Both panels are after dropping the top and bottom 1 percentile for all variables. Medium and large firms are defined according
to the Companies House definition. Growtht=Turnovert/Turnovert-1. ROAt=EBITt/((TotAssetst+TotAssetst-1)/2). Currency
variables are in thousands of GBP. Age is in years. On the top of each panel is the number of firms that belonged to panel's
group at least one period in the sample
Total Assets
Turnover
Profit
CAPEX
Age
Leverage
Growth
ROA
Cash
Total Assets
Turnover
Profit
CAPEX
Age
Leverage
Growth
ROA
Cash
Panel A: Medium and Large Non Quoted (90302)
# Obs
mean
median
sd
min
447614
10684
3812
28534
1401
284564
25421
10594
48497
2801
365302
566
182
2160
-40600
165307
544
111
2435
-17858
482309
24.066
17.208
21.524
0.003
464264
0.61
0.65
0.29
0.00
245653
1.14
1.07
0.42
0.03
336047
0.08
0.07
0.14
-1.43
381575
743
202
2145
0
Panel B: Quoted (2021 firms)
# Obs
mean
median
sd
min
11914
317160
36277
1007877
49
11175
334809
44296
953501
16
11701
13047
1126
52848
-123300
8927
18530
1584
64367
-19834
12140
29.502
14.560
31.597
0.003
11923
0.52
0.51
0.30
0.00
9976
1.31
1.10
1.23
0.10
10527
0.00
0.08
0.28
-2.54
11078
18671
2569
50790
0
-28-
max
6451000
4443000
423000
321000
146.348
3.69
34.33
1.32
490000
max
13500000
10600000
615000
788727
130.137
4.00
25.47
0.54
611000
Table 2
Deals Summary Statistics
Both panels are after dropping the top and bottom 1 percentile for all variables. Panel A (B) are summary of ALL IPO
(Going Private) deals Growtht=Turnovert/Turnovert-1. ROAt=EBITt/((TotAssetst+TotAssetst-1)/2). proxy R&D
=Grossprofit-operating profit. Currency variables are in thousands of GBP. Age is in years.
Panel A: IPO sample (Total 1113, 1111 matched with FAME)
# Obs
mean
median
sd
min
Before IPO
Total Assets
891
54202
4371
250111
0
Turnover
783
58697
5887
231536
0
Profit
828
1188
126
9813
-40600
CAPEX
620
4460
325
18462
-1105
Age
567
8.866
4.118
15.162
0.003
Leverage
866
0.78
0.70
0.57
0.00
Growth
536
1.91
1.28
2.77
0.04
ROA
367
0.04
0.11
0.38
-2.36
proxy R&D
672
5973
2075
13646
-396
After IPO
Total Assets
827
73839
13202
281005
92
Turnover
776
70417
8538
267745
17
Profit
816
709
197
11988
-115600
CAPEX
649
6179
680
22798
-3610
Age
567
9.853
5.118
15.166
0.512
Leverage
833
0.45
0.41
0.35
0.00
Growth
677
1.94
1.26
2.48
0.10
ROA
798
-0.09
0.07
0.44
-2.41
proxy R&D
667
12237
3109
37564
0
Panel B: Going Private Sample (Total 271, 270 matched with FAME)
# Obs
mean
median
sd
min
Before Going Private
Total Assets
239
117144
42052
198472
933
Turnover
233
157398
58283
312212
559
Profit
237
2690
860
13481
-59800
CAPEX
193
8636
2076
19777
-8800
Age
195
35.068
23.926
30.967
0.915
Leverage
238
0.52
0.52
0.21
0.07
Growth
219
1.18
1.05
0.66
0.45
ROA
221
0.05
0.08
0.17
-0.74
Cash
221
8192
2600
18647
2
After Going Private
Total Assets
199
110378
32605
259996
674
Turnover
146
143531
37913
385749
77
Profit
190
1584
-73
18823
-28543
CAPEX
89
4747
1265
8889
-4964
Age
195
36.091
24.929
30.984
1.718
Leverage
199
0.53
0.48
0.39
0.00
Growth
138
0.98
0.98
0.89
0.01
ROA
190
-0.02
0.01
0.25
-1.43
Cash
167
7993
1730
19563
0
-29-
max
3288039
2553000
164000
226000
105.978
3.59
30.78
1.12
161550
4101000
2971827
136000
296074
106.981
3.79
23.80
0.54
518400
max
1230300
2574200
96800
143300
123.337
1.14
6.04
0.45
189800
2966100
3364200
164100
42879
124.337
2.95
10.23
0.74
169100
Table 3
Determinants of the decision to be listed
The effect of the variables listed at time t on the probability to be listed on a stock exchange at t+1. The estimates are from a
probit model. The sample is restricted to all listed firms and unlisted firms that their book value of total assets is bigger than 1400
thousands GBP. Growtht=Turnovert/Turnovert-1. ROAt=EBITt/((TotAssetst+TotAssetst-1)/2). Leverage=1-Equity/TotAssets. MTB
is the median market to book value of equity of listed firms on the LSE in the same industry. The regression also includes a
constant term (not reported). Unquoted=1-Quoted. Currency variables are in mil of GBP. In brackets are z statistics. z statistics
are hetroskedasticity and autocorrelation (within each firm) robust. Age, Turnover and Total Assets are in logs.
Quoted
Unquoted*log(Age)
Quoted*log(Age)
Unquoted*CAPEX
Quoted*CAPEX
Unquoted*Growth
Quoted*Growth
Unquoted*MTB
Quoted*MTB
Unquoted*ROA
Quoted*ROA
Unquoted*Leverage
Quoted*Leverage
Unquoted*Cash
Quoted*Cash
Unquoted*log(TotAsset)
Quoted*log(TotAsset)
All Accts.
4.4281
[16.64]***
-0.3062
[9.88]***
0.0068
[0.23]
0.0145
[2.70]***
0.0026
[2.25]**
0.161
[4.53]***
0.1576
[1.59]
0.0938
[4.09]***
0.2
[4.03]***
0.2241
[0.70]
-0.0773
[0.47]
-0.0274
[0.20]
-0.0059
[0.04]
0.0174
[3.67]***
0.0057
[2.06]**
0.1826
[6.90]***
-0.0778
[2.98]***
Cons. Accts.
4.2903
[15.22]***
-0.2683
[8.02]***
-0.0058
[0.19]
0.0146
[2.63]***
0.0023
[2.12]**
0.1444
[4.04]***
0.1503
[1.48]
0.0772
[2.70]***
0.1981
[3.88]***
-0.0069
[0.02]
-0.0639
[0.39]
0.1624
[1.12]
-0.0284
[0.19]
0.0171
[3.61]***
0.0054
[1.99]**
0.128
[3.94]***
-0.0638
[2.32]**
Unquoted*log(Turnover)
Quoted*log(Turnover)
Observations
Pseudo R2
92969
0.9128
38105
0.8994
*** significant at the 1% level, ** at the 5% level, * at the 10% level
-30-
All Accts.
4.0852
[15.67]***
-0.3182
[10.05]***
0.0205
[0.69]
0.0216
[3.34]***
0.0029
[2.26]**
0.1622
[4.41]***
0.1466
[1.44]
0.0838
[3.65]***
0.1987
[3.97]***
0.1199
[0.40]
0.0624
[0.38]
-0.059
[0.43]
0.1881
[1.10]
0.0232
[4.24]***
0.0063
[2.21]**
Cons. Accts.
3.9881
[14.70]***
-0.2682
[7.92]***
0.0066
[0.22]
0.0194
[3.14]***
0.0026
[2.13]**
0.143
[3.95]***
0.1415
[1.37]
0.0689
[2.40]**
0.1958
[3.82]***
0.002
[0.01]
0.0581
[0.35]
0.1813
[1.24]
0.1375
[0.80]
0.022
[4.24]***
0.006
[2.14]**
0.0532
[1.88]*
-0.1017
[4.23]***
93165
0.9116
0.0063
[0.21]
-0.087
[3.45]***
38270
0.8987
Table 4
Determinants of the decision to be listed - sub samples
The effect of the variables listed at time t on the probability to go public at t+1 for sub samples of the data.
The estimates are from a probit model. The sample is restricted to all unlisted firms that their book value of total
assets is bigger than 1400 thousands GBP. Only consolidated accounts are used. Growtht=Turnovert/Turnovert-1.
ROAt=EBITt/((TotAssetst+TotAssetst-1)/2). Leverage=1-Equity/TotAssets. MTB is the median market to book
value of equity of listed firms on the LSE in the same industry. The regression also includes a constant term
(not reported). Unquoted=1-Quoted. proxyRDabs=(GrossProfit-OperProfit+Depreciation).
proxyRDratio=ProxyRDabs/turnover. Currency variables are in mil of GBP. In brackets are z statistics. z
statistics are hetroskedasticity and autocorrelation (within each firm) robust. Age, Turnover and Total Assets are
in logs.
proxyRDabs
Low R&D
industries
0.0028
[0.51]
High R&D
industries
0.0093
[1.74]*
proxyRDratio
log(Age)
CAPEX
Growth
MTB
ROA
Leverage
Cash
log(TotAsset)
Observations
Pseudo R2
-0.3101
[5.22]***
0.0227
[1.24]
0.1546
[3.67]***
-0.0002
[0.00]
0.0714
[0.11]
0.1769
[0.82]
0.0414
[4.31]***
0.0693
[1.17]
12504
0.18
-0.2167
[4.66]***
0.0207
[2.01]**
0.1076
[3.43]***
0.1481
[4.49]***
-0.0265
[0.05]
0.1649
[0.60]
0.0131
[1.66]*
0.0932
[1.64]
12274
0.1375
Low R&D
industries
High R&D
industries
0.0312
[3.00]***
-0.2959
[4.94]***
0.0234
[1.32]
0.1562
[3.63]***
0.0082
[0.08]
0.3461
[0.51]
0.2286
[1.06]
0.0394
[4.04]***
0.09
[1.52]
12466
0.192
0.0753
[2.49]**
-0.2121
[4.62]***
0.0168
[1.69]*
0.1069
[3.44]***
0.1496
[4.55]***
0.0504
[0.10]
0.223
[0.85]
0.0141
[2.02]**
0.1434
[2.91]***
12269
0.1366
*** significant at the 1% level, ** at the 5% level, * at the 10% level
-31-
Table 5
The effect of Going Public
t+1 is the period immediately after going public. Currency variables are in thousands of GBP. Mtest is the t-stat of the paired test of the
hypothesis that var1 - var2 has a mean of zero. N is the number of observations that var1>var2. Rtest is the z-stat of the hypothesis that
var1-var2 has a median of zero using the Wilcoxon matched-pairs signed-ranks test. proxyRDabs=(GrossProfit-Operating Profitdepreciation). proxyRDratio=proxyRDabs/turnover. Italic is significant at 10%; Bold is significant at 5%; Bold and underlined is
significant at 1%.
Panel A - All IPOs
Var1
CAPEXt+1
CAPEXt+2
CAPEXt+3
Var2
CAPEXt
CAPEXt
CAPEXt
mean Var1
6173.24
5195.23
5769.15
mean Var2
3990.30
3665.43
3485.66
Mean test
3.40
3.56
3.46
N(var1>var2)
353
322
252
Rank test
9.24
8.79
8.05
#Obs
506
464
358
Leveraget+1
Leveraget
0.45
0.78
-16.81
153
-18.22
802
Leveraget+2
Leveraget
0.53
0.78
-11.74
181
-13.99
722
Leveraget+3
Leveraget
0.52
0.78
-11.35
166
-12.30
609
Casht+1
Casht
6556.28
2874.09
7.70
557
15.88
700
Casht+2
Casht
5926.77
2690.80
5.81
480
13.66
627
Casht+3
Casht
6880.44
3008.10
5.02
390
11.45
510
ROAt+1
ROAt
-0.15
-0.11
-0.26
170
-1.41
340
ROAt+2
ROAt
-0.02
-0.20
1.20
132
-2.46
301
ROAt+3
ROAt
-0.01
0.05
-1.24
98
-4.75
262
EBITt+1
EBITt
3604.13
3378.89
0.59
378
-0.24
762
EBITt+2
EBITt
2356.59
2878.58
-1.11
342
-0.29
691
EBITt+3
EBITt
2604.66
3267.55
-1.15
272
-0.51
576
Panel B – Low Deficit IPOs
Var1
CAPEXt+1
CAPEXt+2
Var2
CAPEXt
CAPEXt
mean Var1
mean Var2
Mean test
N(var1>var2)
Rank test
#Obs
2607.59
1693.03
3.13
110
5.74
152
3789.48
1738.35
2.04
94
6.70
128
CAPEXt+3
Leveraget+1
Leveraget+2
Leveraget+3
Casht+1
Casht+2
Casht+3
ROAt+1
ROAt+2
ROAt+3
EBITt+1
EBITt+2
EBITt+3
CAPEXt
Leveraget
Leveraget
Leveraget
Casht
Casht
Casht
ROAt
ROAt
ROAt
EBITt
EBITt
EBITt
3694.90
0.50
0.53
0.49
5692.84
4394.35
4474.47
0.00
-0.02
-0.04
2104.31
1103.15
1084.51
1056.97
0.68
0.69
0.68
1994.13
1878.21
1972.07
0.08
0.20
0.27
2311.21
2306.72
2180.34
3.46
-7.54
-5.10
-5.49
3.49
5.31
3.65
-0.68
-3.07
-5.75
-0.32
-1.27
-1.04
78
36
30
30
111
102
80
61
40
24
91
77
53
6.16
-7.34
-5.71
-6.17
7.46
6.83
5.43
-2.11
-4.23
-6.53
1.80
1.19
-1.06
97
159
135
118
143
125
107
132
114
99
160
137
116
-32-
Table 5 continued
Panel C - High Deficit IPOs
Var1
CAPEXt+1
CAPEXt+2
CAPEXt+3
Leveraget+1
Leveraget+2
Leveraget+3
Casht+1
Casht+2
Casht+3
ROAt+1
ROAt+2
ROAt+3
EBITt+1
EBITt+2
EBITt+3
Var2
CAPEXt
CAPEXt
CAPEXt
Leveraget
Leveraget
Leveraget
Casht
Casht
Casht
ROAt
ROAt
ROAt
EBITt
EBITt
EBITt
mean Var1
8223.62
6743.37
8023.51
0.45
0.51
0.51
7987.54
8428.76
8187.45
-0.52
-0.04
-0.01
4920.76
3793.43
4019.40
mean Var2
5190.58
3871.90
4687.77
0.77
0.75
0.73
3685.14
2630.13
3087.02
-0.37
-0.34
-0.23
4421.73
3612.41
4399.03
Mean test
3.06
3.47
3.03
-8.25
-6.79
-5.72
4.25
3.45
3.26
-0.64
2.37
1.90
0.85
0.13
-0.23
N(var1>var2)
102
87
69
26
31
26
114
93
81
66
54
41
89
83
64
Rank test
4.62
4.38
4.42
-8.57
-7.36
-6.09
6.59
5.73
5.11
0.62
0.92
0.21
1.27
2.10
1.53
#Obs
156
134
99
160
141
115
153
134
106
116
99
84
161
142
115
N(var1>var2)
194
196
153
130
112
96
Rank test
9.31
11.13
10.05
1.88
2.03
1.83
#Obs
240
219
176
230
203
163
N(var1>var2)
243
245
198
138
139
124
Rank test
10.13
11.90
11.19
1.52
1.96
1.90
#Obs
299
280
226
276
253
213
Panel D - Low R&D industries
Var1
Var2
proxyRDabst+1
proxyRDabst
proxyRDabst+2
proxyRDabst
proxyRDabst+3
proxyRDabst
proxyRDratiot+1
proxyRDratiot
proxyRDratiot+2
proxyRDratiot
proxyRDratiot+3
proxyRDratiot
Var1
Var2
proxyRDabst+1
proxyRDabst
proxyRDabst+2
proxyRDabst
proxyRDabst+3
proxyRDabst
proxyRDratiot+1
proxyRDratiot
proxyRDratiot+2
proxyRDratiot
proxyRDratiot+3
proxyRDratiot
mean Var1
7863.72
11151.17
14232.26
1.37
1.15
0.75
mean Var2
6019.55
5920.32
6098.80
2.07
7.99
0.75
Mean test
3.96
6.14
6.71
-1.38
-1.00
0.00
Panel E - High R&D industries
mean Var1
7159.67
11556.46
13618.06
1.38
1.57
1.70
mean Var2
5136.22
5149.96
4920.71
6.15
6.55
0.93
-33-
Mean test
5.04
4.04
4.48
-1.29
-1.23
1.07
Table 6
The effect of Going Private
t+1 is the period immediately after going public. Currency variables are in thousands of GBP. Mtest is the t-stat of the paired test of the
hypothesis that var1 - var2 has a mean of zero. N is the number of observations that var1>var2. Rtest is the z-stat of the hypothesis that var1var2 has a median of zero using the Wilcoxon matched-pairs signed-ranks test. Italic is significant at 10%; Bold is significant at 5%; Bold and
underlined is significant at 1%.
Var1
CAPEXt+1
CAPEXt+2
CAPEXt+3
Var2
CAPEXt
CAPEXt
CAPEXt
mean Var1
5362.66
4776.23
6366.00
mean Var2
6778.74
6400.55
7105.71
Mean test
-1.55
-1.25
-0.20
N(var1>var2)
28
17
15
Rank test
-1.76
-1.22
0.77
#Obs
74
40
24
Leveraget+1
Leveraget+2
Leveraget+3
Casht+1
Casht+2
Casht+3
ROAt+1
ROAt+2
ROAt+3
EBITt+1
EBITt+2
EBITt+3
Leveraget
Leveraget
Leveraget
Casht
Casht
Casht
ROAt
ROAt
ROAt
EBITt
EBITt
EBITt
0.53
0.49
0.50
7329.61
5389.55
4357.89
-0.05
0.07
0.13
4038.10
5947.90
9315.62
0.53
0.53
0.55
9224.02
10369.91
9178.74
0.06
0.05
0.09
7783.09
7157.32
7179.21
-0.20
-1.57
-1.27
-1.71
-2.58
-2.36
-1.97
0.76
0.92
-3.13
-0.71
0.51
89
70
53
70
43
27
54
69
45
64
72
54
-1.71
-2.55
-1.70
-1.61
-3.29
-3.03
-6.08
-0.98
-1.40
-4.94
-0.57
-0.80
195
165
119
156
116
76
177
146
103
188
155
112
-34-