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Internet Penetration and International IPO Underpricing
Thomas J. Boultona,*, Scott B. Smartb, Chad J. Zutterc
aFarmer School of Business, Miami University, Oxford, OH 45056, USA bKelley School of Business, Indiana University, Bloomington, IN 47405, USA
cKatz Graduate School of Business, University of Pittsburgh, Pittsburgh, PA 15260, USA
Draft: September 2015
Abstract
We study the relation between Internet penetration and initial public offering (IPO) underpricing. Examining 9,432 IPOs from 34 countries, we find that IPO offer prices are more precise in countries where more people have access to the Internet. Internet penetration is negatively correlated with initial returns and positively associated with the size of outside blockholdings for at least one year after the IPO. These findings are consistent with the conjecture that Internet access is associated with reduced information asymmetry and, therefore, more efficient IPO outcomes.
JEL classification: G15; G24; G30; G32; G34
Keywords: international finance; Internet penetration; information asymmetry; initial public offerings; underpricing
Research funding was provided by the Lindmor Professorship (Boulton). Any remaining errors or omissions
are the responsibility of the authors.
* Corresponding author. Tel.: + 1-513-529-1563.
E-mail address: boultotj@miamioh.edu (T. Boulton).
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I. Introduction
The world has witnessed dramatic changes in the speed of information availability and methods for
consuming information in recent decades. Arguably, the most impactful change in information
consumption is a result of the advent of the Internet, which makes information available almost
instantaneously to an unprecedented number of people around the world. The important role the Internet
plays in information consumption is illustrated by a recent study from the American Press Institute, which
finds that more Americans use a computer to access news stories each week (69 percent) than traditional
sources like radio (65 percent) and print newspapers / magazines (61 percent).1 Widespread use of the
Internet began in the United States and many other developed countries in the mid-1990s. However,
Internet penetration has not been constant across the world through time. According to statistics compiled
by The World Bank that we summarize in Figure 1, Internet penetration (i.e., Internet users per 100
people) grew from 30 percent to 74 percent in the United States from 1998 to 2008. However, Internet
penetration levels remained below 50 percent in many countries as of 2008, including Argentina, Brazil,
China, India, Italy, Portugal, and Thailand.
[Place Figure 1 about here]
Research finds that the Internet has had profound effects on several markets, including life insurance
(Brown and Goolsbee, 2002), automobiles (Zettelmeyer, Morton, and Silva-Risso, 2006), used books
(Ghose, Smith, and Telang, 2006), and airlines (Orlov, 2011). Common takeaways from this literature are
that the Internet reduces the cost of information acquisition, lessens information asymmetry, helps
overcome adverse selection problems, and leads to more competitive markets. For example, Zettelmeyer,
Morton, and Silva-Risso (2006) show that the Internet lowers prices in the retail automobile market by
providing better information to consumers and changing the means of price negotiations. We contribute to
this literature by studying the impact of the Internet on the capital markets, where information asymmetry
and adverse selection inhibit the efficient allocation of resources. Specifically, we leverage cross-country
1 http://www.americanpressinstitute.org/publications/reports/survey-research/how-americans-get-news/
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variation in the rate of Internet penetration to examine the role of information asymmetry in the market
for initial public offerings (IPOs), a capital market transaction characterized by severe information
asymmetry problems.
Information asymmetry is believed to impact the IPO process in many ways, including the precision
of offer prices and the substantial first-day returns exhibited by many new issues. On the issue of offer
price precision, Bradley, Cooney, Jordan, and Singh (2004) find robust evidence that firms are more
likely to set an integer offer price when there is a high degree of uncertainty surrounding firm value.
Several theories suggest that information disparities among IPO participants drive first-day gains,
including information asymmetries between issuers and investment banks (Barron, 1992), issuers and
investors (Welch, 1989), and more- and less-informed investors (Rock, 1986). Ljungqvist (2007) weighs
the evidence in the IPO literature and concludes that information asymmetry has a “first-order effect on
underpricing.” (p. 380) If greater Internet penetration is associated with better information dissemination
and, therefore, less information asymmetry, then we should observe a negative relation between Internet
penetration and both the frequency of integer offer prices and IPO underpricing.
We test our hypothesis using a sample of 9,432 IPOs issued in 34 countries from 1998 to 2008. Our
measure of Internet penetration is from The World Bank, which began reporting the number of Internet
users per 100 people on a country-by-country basis annually in the mid-1990s. Consistent with the idea
that Internet access reduces information asymmetry, we find that firms are less likely to set an integer
offer price in countries with greater Internet penetration. Unconditionally, slightly more than half of our
sample IPOs are priced on an integer (50.4 percent). The results of logistic regressions indicate that a one
standard deviation increase in Internet penetration, which is equivalent to adding over 23 Internet users
per 100 people, is associated with a 2.3-4.6 percent decrease in the likelihood that an IPO firm sets an
integer offer price.
When we consider initial returns, we find a negative association between country-level measures of
Internet penetration and firm-level underpricing. In other words, in countries where more people have
access to information via the Internet, IPO firms tend to experience smaller first day returns. This is
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consistent with prior literature that finds a positive relation between information asymmetry and initial
returns. The effect of Internet penetration on underpricing is both statistically and economically
significant. As a point of reference, the average underpricing for our IPO sample is slightly over 39
percent. Our multivariate results imply that a one standard deviation increase in Internet penetration is
associated with a 16 percentage point decrease in underpricing.
The relation between Internet penetration and underpricing is robust to measuring initial returns over
the first 22 trading days (one calendar month). Measuring returns over the first calendar month
simultaneously controls for daily volatility limits imposed in several sample countries and underwriters’
propensity to engage in price stabilization. When we include country-level trust measures available from
The World Values Survey, we find that the negative relation between Internet penetration and
underpricing is stronger in countries with higher levels of trust. We interpret this result to suggest that
information received online is viewed as more credible in countries with higher levels of trust.
In addition to the relation between Internet penetration and underpricing, we consider the role of
information asymmetry on post-IPO blockholdings. If information asymmetry deters investors from
taking large stakes in IPO firms, we expect to observe a positive relation between Internet penetration and
post-IPO blockholdings. If, on the other hand, information asymmetry motivates larger post-IPO
blockholdings by giving post-IPO investors greater influence over corporate matters, we should observe a
negative relation between Internet penetration and post-IPO blockholdings. Our evidence is consistent
with the former. Specifically, we find that ownership concentration is positively correlated with Internet
penetration at least one year after the IPO. As one might expect, this relation dissipates as time passes
from the initial public offering and information asymmetry is resolved in the market.
Our study contributes to the literature in several ways. First, we provide evidence that Internet
penetration is correlated with capital-market outcomes. This complements prior research that documents
that the Internet has had a positive effect on other markets, including life insurance (Brown and Goolsbee,
2002), automobiles (Zettelmeyer, Morton, and Silva-Risso, 2006), used books (Ghose, Smith, and Telang,
2006), and airlines (Orlov, 201). We show that IPO offer prices are more precise and that initial returns
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tend to be lower in countries where Internet access is more widespread. Our results imply that countries
that invest in Internet availability may experience positive spillover effects in the capital markets, as the
cost of going public decreases for firms seeking to raise equity capital.
Second, we contribute to the literature on the determinants of cross-country variation in IPO
outcomes. Take underpricing, for example, which is observed in all countries and time periods, with
substantial variation in average initial returns around the world (e.g., Loughran, Ritter, and Rydqvist,
1994). Prior studies consider differences in country-level institutional characteristics (Loughran, Ritter,
and Rydqvist, 1994; Boulton, Smart, and Zutter, 2010) and accounting outcomes (Boulton, Smart, and
Zutter, 2011) as partial explanations for this cross-country variation. Our results suggest a more basic
determinant, access to abundant and timely information via the Internet, helps to explain the cross-country
variation in initial returns. We also believe that we are the first to study IPO offer price precision in an
international sample. Our results suggest that, in addition to firm- and event-specific factors, country-level
characteristics have the potential to impact IPO firms’ pricing decisions.
Third, in addition to our main results on the relation between Internet penetration, offer price
precision, and IPO underpricing, we find that Internet penetration is positively correlated with post-IPO
blockholdings. Outside blockholders are believed to have a positive impact on corporate policy (Barclay
and Holderness, 1991; Dennis Serrano, 1996; Bethel, Liebeskind, and Opler, 1998). Our results suggest
that more widespread access to the Internet may lead to greater oversight of management by outside
blockholders. Thus, in addition to a lower cost of going public, greater Internet access appears to play a
positive role in firm-level governance.
The remainder of the paper is organized as follows. We discuss the related literature and develop
hypotheses in Section II. In Section III, we describe our data and empirical strategy. Section IV reports
our empirical results. Section V offers our conclusions.
II. Internet penetration and IPOs
Information asymmetry in initial public offerings
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Prior research suggests that information asymmetry problems exist between IPO firms, financial
intermediaries, and investors (e.g., Barron, 1992; Welch, 1989; Rock, 1986). Several studies report
evidence to suggest that IPO firms take actions to reduce information disparities and improve IPO
outcomes. Avenues considered for reducing information asymmetry include providing more timely and
informative disclosures to investors (Jog and McConomy, 2003; Schrand and Verrecchia, 2005; Leone,
Rock, and Willenborg, 2007) and associating with more reputable financial intermediaries (Beatty and
Ritter, 1986; Carter and Manaster, 1990; Megginson and Weiss, 1991). These, and related studies, tend to
find evidence consistent with the idea that improved disclosures and reputable financial intermediaries
reduce information asymmetry among IPO participants.
Our study extends the analysis to a multi-country setting to determine if country-level Internet
penetration is correlated with information asymmetry and IPO outcomes in different markets. In so doing,
we add to the limited evidence on the determinants of cross-country IPO outcomes and to the literature on
the value of information dissemination in different countries. Given the central role of asymmetric
information in new issues, we anticipate that differences in Internet penetration across countries will
influence the costs that firms going public in different countries face.
Our first hypothesis considers the relation between country-level Internet penetration and the
precision of IPO offer prices. Harris (1991) studies stock price clustering and discreteness and proposes
that traders use discrete prices to simplify and lower the cost of negotiations. Bradley, Cooney, Jordan,
and Singh (2004) extend this line of reasoning to IPO offer prices in the U.S. and find that a significant
portion of firms set an integer offer price. Consistent with the notion that integer offer prices suggest
greater value uncertainty, the authors find a positive relation between integer offer prices and offer price
adjustments, initial returns, and post-IPO return volatility. If Internet penetration reduces uncertainty by
providing superior information for issuers and underwriters, we should expect IPO firms to be less likely
to set an integer offer price in countries with greater Internet penetration. This leads us to our first
hypothesis:
H1: Internet penetration is positively correlated with offer price precision.
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Our second hypothesis studies the relation between country-level Internet penetration and IPO initial
returns. Theory suggests that information disparities among IPO participants drive first-day gains,
including information asymmetries between issuers and investment banks (Barron, 1992), issuers and
investors (Welch, 1989), and more- and less-informed investors (Rock, 1986). For example, Rock (1986)
suggests that underpricing is necessary to induce less-informed investors to participate in the new issues
market, lest they withdraw from the IPO market entirely. Consistent with the notion that better
information is associated with lower underpricing, Schrand and Verrecchia (2005) report lower
underpricing when firms make more frequent pre-IPO disclosures and Leone, Rock, and Willenborg
(2007) find lower underpricing for issuers with more specific “use of proceeds” disclosure. This leads to
our second hypothesis, which predicts a negative relation between Internet penetration and underpricing.
H2: Internet penetration is negatively correlated with initial returns.
Our third hypothesis considers the impact of Internet penetration on post-IPO ownership
concentration, which is not immediately apparent. On the one hand, more information may encourage
greater IPO participation and smaller blockholdings, as investors do not feel compelled to hold large
blocks as a means of securing greater access to information. On the other hand, more information may
encourage investors to take larger positions in firms in which they feel more informed, resulting in larger
post-IPO blockholdings. Thus, our third hypothesis reflects uncertainty with respect to the relation
between Internet penetration and post-IPO blockholdings.
H3: Internet penetration is positively / negatively correlated with post-IPO blockholdings.
In the next section we describe the sample we construct to test our hypotheses. Subsequent sections
provide evidence consistent with the notion that greater Internet penetration is associated with more
efficient IPO outcomes.
III. IPO sample
Sample construction
We begin our sample construction by retrieving all IPOs for all countries reported in the Thomson
Financial SDC Platinum New Issues database from 1998 through 2008. As is custom in the IPO literature,
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we exclude financial firms, rights offerings, unit offerings, closed-end funds, trusts, limited partnerships,
and depository receipts. IPO events are matched with the Datastream database using the SEDOL
identifier common to both databases or by hand where the SEDOL is not available. For each match, we
collect the first-day secondary market price, which we define as the first closing price with positive
trading volume that occurs within –3 to +60 days of the SDC IPO issue date, required to calculate
underpricing. We drop IPOs that do not have a valid “first-day” secondary market closing price in
Datastream and IPOs issued in countries not uniquely covered by The World Bank’s Internet penetration
data.2 To eliminate the impact of outliers, we trim our sample by removing the top and bottom one
percent based on initial returns, which are calculated as the first-day secondary market closing price
divided by the IPO offer price, minus 1. Finally, we exclude countries with fewer than five IPOs during
our sample period, leaving us with a final sample of 9,432 IPOs issued in 34 countries.
Descriptive statistics
In Table 1, we report descriptive statistics for the variables used in our analysis. Mean Internet
penetration across our IPO sample is 44.6, indicating that the typical sample IPO event takes place in a
country where slightly more than 44 out of every 100 people has Internet access at the time of the
offering. The cross-sectional standard deviation of Internet penetration is 23.4 percent, indicating large
variation in access to the Internet across our sample.
[Place Table 1 about here]
Because other sources of information may serve to reduce information asymmetry, we consider
newspaper circulation as an alternative measure. Newspaper circulation data is from the UNESCO
Institute for Statistics, which reports total average circulation per 1,000 inhabitants. Because updated data
on newspaper subscriptions is not available for our entire sample period for many countries, we use the
newspaper circulation statistic reported closest to but not after 1997 for each of our sample countries. As
2 Due to daily volatility limits that may constrain secondary prices, we use the tenth valid price to measure
underpricing for IPOs issued in France and Greece.
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was the case with Internet penetration, there is substantial variation in access to information across our
sample countries based on newspaper circulation. The sample mean is 2.9 newspapers per 1,000
inhabitants, with a range of 0.3 to 15.1. Unlike Internet penetration, which increased in every sample
country during our period of investigation, newspaper circulation was stable or even declined during the
same period in many of our sample countries.
Trust is from The World Values survey, which asks: “Generally speaking, would you say that most
people can be trusted or that you can’t be too careful in dealing with people?” On average, 37.2 percent of
respondents indicate that people can be trusted. However, this measure exhibits substantial variation, with
a range of 2.8 percent to 68.0 percent within our sample. The sample mean initial return equals 39.1
percent. Not evident in Table 1 is the substantial variation in average first day returns across countries
previously documented by Loughran, Ritter, and Rydqvist (1994) and others. We illustrate the cross-
country variation in initial returns and the number of IPOs for our sample in Figure 2. Average first day
returns range from 1.4 percent in Argentina to 120.7 percent in China during our sample period.
[Place Figure 2 about here]
Bradley, Cooney, Jordan, and Singh (2004) indicate that IPOs priced on an integer signal greater
value uncertainty and exhibit greater underpricing. We find that slightly more than half of our IPOs have
an integer offer price. We create an indicator variable to identify top-tier underwriters, based on prior
research that finds that underpricing may be influenced by the quality of the underwriter (e.g., Carter and
Manaster, 1990; Megginson and Weiss, 1991). Top tier underwriter is set equal to one for IPOs
underwritten by investment banks listed in the top 25 of SDC’s global league tables for the issue year, and
zero otherwise. Fewer than 25 percent of our IPOs employ a top-tier underwriter.
Price stabilization refers to underwriters’ tendency to provide price support once IPO trading begins.
The incentive to engage in price stabilization is especially true for IPOs that experience a price decline
that threatens to breach the offer price. Price stabilization activity would temporarily inflate secondary
market prices, resulting in larger initial returns. If price stabilization is widespread, then we expect to see
more first-day returns equal to or slightly greater than zero and fewer first-day returns just below zero as
9
underwriters participate in post-IPO trading to prevent prices from dropping below the offer price.
Therefore, for each country, we calculate price stabilization, which is the difference in the number of
IPOs with initial returns between zero and one percent and the number of IPOs with initial returns
between zero and negative one percent. We normalize this difference by dividing by the total number of
IPOs in each country. In countries where price stabilization is common, we expect larger values for price
stabilization, and larger underpricing. The sample mean value for price stabilization is 0.01, which
indicates a slight tendency towards stabilization.
“Hot market” effects suggest higher underpricing during periods when IPO volume and overall stock
market returns are high (e.g., Ritter, 1984). To control for these hot market effects, we construct an IPO
activity measure, which equals the number of IPOs in a given country in each year divided by the total
number of listed equities in Datastream for that country in 2008. The sample mean value for IPO activity
is 0.027, which indicates that there are 2.7 IPOs for every 100 publicly listed firms in the issue year of our
average sample IPO. As a second control, we calculate the return on the Datastream market index in the
three months preceding each IPO. We report a mean return of 2.9 percent over the three months leading
up to the typical sample IPO.
To control for differences in liquidity across national markets, we include a stock market turnover
ratio, which is updated annually for each sample country by The World Bank. Ellul and Pagano (2006)
suggest that IPOs in less liquid markets will exhibit larger initial returns, as underpricing, in part,
compensates IPO investors for the illiquidity risk that they bear. The sample mean indicates that the
typical sample country experiences a total value of shares traded equal to 102.2 percent of its average
market capitalization over the calendar year. La Porta et al. (2000) demonstrate a link between investor
protections and capital market outcomes. In the context of IPO markets, Boulton, Smart, and Zutter
(2010) find that IPOs tend to be underpriced more in countries with strong shareholder protections. We
control for country-level governance by including the antidirector rights index from La Porta et al. (1998).
Offer size is included to capture information asymmetries. The intuition for this variable is that larger
IPOs are often sold by firms that are more familiar to investors and tend to generate more discussion in
10
the period preceding the offer date. We CPI-adjust the offer size reported by SDC to constant 2008 U.S.
dollars using CPI data from the U.S. Bureau of Labor Statistics website. The average IPO in our sample
raises slightly more than $107 million. Volatility captures the standard deviation of returns over the 30
days following the IPO. Average volatility is 4.9 percent.
We include an indicator variable that identifies bookbuilt offerings, which Sherman (2005) finds is
the prominent method for taking firms public worldwide. Over 65 percent of our sample IPOs are book-
built. In our sample, 54.5 percent of IPOs are firm commitment, which Ritter (1987) finds are underpriced
less than best efforts IPOs. Few IPOs are equity carve-outs (3.6 percent), which Schipper and Smith
(1986) and Prezas, Tarimcilar, and Vasudevan (2000) find are underpriced less than original IPOs. We
also consider the monitoring role of commercial banks, who may substitute for shareholder monitoring,
especially when they can make equity investments. Based on information reported in Barth, Caprio, and
Levine (2006), 41.4 percent of sample IPOs are issued in countries that permit bank ownership of equity.
Based on the classifications of Ljungqvist and Wilhelm (2003), 24.2 percent of IPOs are from a hi tech
industry.
IV. Internet penetration and IPOs
Country-level Internet penetration and IPO offer price precision
Our first hypothesis predicts a positive relation between country-level Internet penetration and the
precision of IPO offer prices. Harris (1991) studies stock price clustering and discreteness and proposes
that traders use discrete prices to simplify and lower the cost of negotiations. Bradley, Cooney, Jordan,
and Singh (2004) extend this line of reasoning to IPO offer prices and find that a significant portion of
firms set an integer offer price. Consistent with the notion that integer offer prices suggest greater
uncertainty, the authors find a positive relation between integer prices and offer price adjustments, initial
returns, and post-IPO return volatility.
In Table 2, we report multivariate analysis that considers the relation between Internet penetration and
the likelihood of observing an integer offer price. Our control variables are inspired by Bradley, Cooney,
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Jordan and Singh (2004), who model the decision to price on an integer as a function of the level of the
final offer price, ex post uncertainty, offer price adjustment, underwriter reputation, and offer size. The
dependent variable in the Table 2 regressions is an indicator variable set equal to one for IPOs priced on
an integer, and zero otherwise. Medium (high) offer price is an indicator variable set equal to one for
IPOs priced at or above the 50th (75th) percentile, within country. Volatility is the standard deviation of
aftermarket return volatility, measured over the first 22 post-IPO trading days. The remaining control
variables are described in conjunction with Table 1. In addition to offer price level, ex post uncertainty,
underwriter reputation, and offer size, we control for recent IPO activity, stock market turnover, and hi
tech firms. Recent IPO activity may provide information to subsequent IPOs that allow for more precise
offer prices. Turnover captures market liquidity, where liquid markets are expected to provide more
immediate feedback and more efficient stock prices to investors. Hi tech is included to capture differences
in uncertainty related to the nature of hi tech firms.
[Place Table 2 about here]
Hypothesis 1 predicts a negative relation between Internet penetration and the likelihood that an IPO
is priced on an integer. Thus, the explanatory variable of interest is Internet penetration and the expected
sign of the coefficient is negative. Consistent with expectations, we find that firms are less likely to set an
integer offer price in countries with greater Internet penetration. The results indicate that a one standard
deviation increase in Internet penetration, which is equivalent to adding over 23 Internet users per 100
people, is associated with a 2.3-4.6 percent decrease in the likelihood of setting an integer offer price.
The control variables are generally consistent with prior literature. Firms that set prices above the
median are more likely to price on an integer compared to IPOs priced below the median. Aftermarket
volatility and underwriter reputation are positively correlated with integer offer prices. Consistent with the
idea that prior IPO activity helps subsequent IPOs set more precise offer prices, recent IPO activity is
negatively correlated with integer offer prices. Contrary to the findings of Bradley, Cooney, Jordan, and
Singh (2004), we find that larger IPOs are more likely to price on an integer. Finally, turnover and hi tech
are both positively associated with integer offer prices.
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The results we report in Table 2 are consistent with the idea that widespread Internet access reduces
information asymmetry in such a way the IPO firms and their intermediaries tend to set more precise offer
prices. In the next section, we consider the relation between Internet penetration and initial returns.
Country-level Internet penetration and IPO underpricing
Our second hypothesis predicts a negative relation between country-level Internet penetration and
firm-level IPO underpricing. Figure 3 reports a simple test of this prediction. We begin by dividing our
IPO sample into terciles based on Internet penetration. Mean internet penetration in the highest tercile is
63.7 (Internet users per 100 people). This compares to 49.3 and 29.2 for the middle and lowest terciles,
respectively. Within each tercile, we calculate average underpricing. Consistent with our prediction, we
find a negative relation between Internet penetration and underpricing. Specifically, average underpricing
is 27.2 (44.9) percent for IPOs in the highest (lowest) tercile of Internet penetration. The difference in
underpricing between the top and bottom terciles is significant at the 1 percent level or better.
[Place Figure 3 about here]
Of course, the evidence reported in Figure 3 fails to control for other factors thought to impact
underpricing. We report a more rigorous examination of the relation between Internet penetration and
underpricing in Table 3. We report the results of multivariate models that control for other determinants
of underpricing discussed in relation to Table 1. The dependent variable in each of the models is
underpricing. The primary variable of interest is Internet penetration. All regressions include industry
controls based on the classifications reported in Dyck and Zingales (2004) and issue year indicator
variables. Statistical significance is based on standard errors clustered at the country level (Rogers, 1993).
[Place Table 3 about here]
Model 1 provides support for our hypothesis that predicts a negative relation between country-level
Internet penetration and firm-level underpricing. The coefficient (–0.007) indicates that a one standard
deviation increase in Internet penetration, which is essentially the equivalent of moving from Malaysia to
the United Kingdom based on 2008 Internet penetration figures, is associated with a 16.4 percentage point
13
decrease in underpricing. This is an economically significant result, considering that the average
underpricing across our IPO sample is 39.1 percent.
As an alternative to Internet penetration, Model 2 considers the relation between newspaper
circulation and underpricing. Consistent with expectations, the relation between newspaper circulation
and underpricing is negative. However, the coefficient is not significant at standard levels. When we
control for both Internet penetration and newspaper circulation in Model 3, we find results similar to
Models 1 and 2. Specifically, the negative relation between Internet penetration and underpricing is
similar in magnitude to Model 1 and statistically significant, while the relation between newspaper
circulation and underpricing is not statistically significant. Presumably, the amount and timeliness of
information available via the Internet is superior to that offered by newspapers. It is also often the case
that the content in newspapers is available online in conjunction with or even in advance of the actual
newspaper printing.
The control variables are consistent with expectations based on prior research. Consistent with hot
markets effects, underpricing is positively correlated with both prior IPO activity and recent market
returns. Consistent with the notion that larger offers suffer less from information asymmetry, we find a
negative relation between offer size and underpricing. Finally, the negative relation between the bank
ownership indicator and underpricing is consistent with Boulton, Smart, and Zutter (2010), which posits
that bank ownership of equity can have a certification effect resulting in lower underpricing. The R-
square values indicate that our models explain about 16 percent of the variation in the international
underpricing cross-section.
Country-level Internet penetration and post-stabilization returns
In Table 4, we report a slightly different specification to study the relation between Internet
penetration and underpricing. Specifically, we measure initial returns using the stock price at the close of
trading 22 trading days (one calendar month) after the initial public offering. This accounts for two
factors that might impact our results. First, several sample countries impose daily volatility limits that
14
may dampen daily price movements for IPO firms (e.g., France, Greece, and Taiwan). After 22 trading
days, the secondary market price should have adjusted fully, even in countries with daily volatility limits.
Second, this approach controls for price stabilization, which consists of post-IPO trading by underwriters
aimed at supporting the secondary market price. Because stabilization activities tend to be short lived, the
impact of price stabilization on IPO returns should diminish over time. As in the prior table, the primary
variable of interest is Internet penetration. The remaining control variables mirror those discussed for
Table 3.
[Place Table 4 about here]
The results reported in Table 4 provide additional support for our main hypothesis. We find a strong,
negative relation between country-level Internet penetration and firm-level IPO returns measured after 22
trading days. The coefficient on the Internet penetration variable reported in Model 1 (–0.008) indicates
that a one standard deviation increase in Internet penetration, is associated with a 18.7 percentage point
decrease in one-month returns, which is slightly larger than the magnitude of the effect when we measure
returns over the first trading day.
The control variables are also consistent with Table 3. One-month returns are positively correlated
with both prior IPO activity and recent market returns, and negatively correlated with offer size. We
continue to find a negative relation between bank ownership of equity and returns. There is also some
evidence that returns are lower for equity carve-outs and higher for hi tech firms. The R-square values
indicate that our models explain about 12 percent of the variation in the international cross-section of
initial returns.
Country-level Internet penetration, trust, and IPO underpricing
The role of Internet penetration in alleviating information asymmetry for IPOs depends, in part, on
whether or not investors trust information received online. In a 2012 Harris Interactive survey, 98 percent
15
of respondents expressed a distrust of the Internet.3 We consider the impact of trust on underpricing and
the relation between Internet penetration and IPO underpricing in Table 5. While not the focus of this
analysis, the role that trust plays in explaining country-level variation in underpricing is also novel. Prior
research finds that cultural attributes help explain country-level differences in underpricing (e.g., Costa,
Crawford, and Jakob (2013), but to our knowledge we are the first to directly examine the relation
between country-level trust and firm-level underpricing.
[Place Table 5 about here]
Our trust measure is from The World Values survey, which asks: “Generally speaking, would you say
that most people can be trusted or that you can’t be too careful in dealing with people?” In Model 1, trust
is continuous measure that reflects the percentage of respondents who answered that most people can be
trusted. In subsequent models, we construct indicator variables for above median and above 75th
percentile trust scores (constructed in sample). The dependent variable is underpricing, although the
reported results are quantitatively similar when we measure returns over the first 22 calendar days, as in
Table 4. The primary variables of interest are Internet penetration and trust, and the interaction of the two.
While we have no priors with respect to the relation between trust and underpricing, if information
received online is viewed as more credible in countries with higher trust scores, we expect to find that the
relation between Internet penetration and underpricing is stronger in countries with higher trust.
Alternatively, if less information is required by investors in high trust countries, it might be the case that
Internet penetration is more impactful in low trust countries. If trust is required for online information to
be viewed as credible, we expect to observe a negative coefficient on the interaction term. Alternatively,
if trust reduces the need for additional sources of information (e.g., online), we expect to observe a
positive coefficient on the interaction term.
Consistent with the notion that information received online is viewed as more credible in countries
that have higher levels of trust, we find that the negative relation between Internet penetration and
3 http://newsfeed.time.com/2012/07/23/almost-everyone-doesnt-trust-the-internet/
16
underpricing is strongest in countries with higher trust scores. This is the case whether we measure trust
using the continuous measure from The World Values Survey (Model 1) or an indicator variable
identifying countries in the top 25 percent based on trust (Model 3). Interestingly, trust alone is positively
correlated with underpricing.
Country-level Internet penetration and post-IPO ownership concentration
As hypothesis 3 reflects, the anticipated impact of Internet penetration on post-IPO ownership
concentration is uncertain. On the one hand, more information may encourage smaller blockholdings, as
outsiders do not feel compelled to hold large blocks as a means of securing greater access to information.
On the other hand, more information may result in larger blockholdings, as investors are more
comfortable taking larger positions in firms in which they feel more informed.
In Table 6, we empirically examine the relation between Internet penetration and post-IPO
blockholdings. The models are motivated by Boulton, Smart, and Zutter (2010), which finds that
underpricing is positively correlated with post-IPO ownership dispersion. The dependent variable in
Models 1-3 is the log of the ratio of the ownership Herfindahl index to 1 minus the ownership Herfindahl
index. The ownership Herfindahl index is the sum of the squared fractional ownership of the following
groups: government, cross holdings, pension funds, investment companies, employee and family, foreign
holdings, and others. Ownership data is from Datastream. By construction, the ownership Herfindahl
index ranges from 0 to 1, with higher values indicative of a more concentrated post-IPO ownership
structure. As an alternative to the ownership Herfindahl index, we calculate the percentage of shares held
in blocks of 5% or more minus employee and family holdings (outside blockholdings). The dependent
variable in Models 4-6 is the log of the ratio of outside blockholdings to 1 minus the outside
blockholdings.
[Place Table 6 about here]
The control variables include initial return, which Brennan and Franks (1997) and Boulton, Smart,
and Zutter (2010) find is correlated with greater post-IPO ownership dispersion in the U.K. and
17
internationally, respectively. Because the cost of accumulating a large block increases for larger offers,
we control for offer size. Top-tier controls for underwriter reputation, which is correlated with their
network for placing shares in an IPO. Stock market turnover controls for stock market liquidity.
Underdevelopment is from Butler and Fauver (2006), who construct a multidimensional development
index that includes the following five dimensions of development: workforce deployment, health,
education, technological infrastructure, and transportation infrastructure. Indicator variables are set equal
to one for equity carve-out deals and government owned companies. Employee/family ownership is the
percentage of shares held by employee and family members, as reported by Datastream.
The positive coefficient on Internet penetration in Models 1, 2, 4, and 5, suggests that greater Internet
access is associated with a more concentrated post-IPO ownership structure. This is effect persists in the
data at least 1 year after the offering. Not surprisingly, the impact of Internet penetration on post-IPO
concentration dissipates as time elapses. The control variables are generally consistent with prior
literature. Specifically, initial returns are negatively correlated with post-IPO blockholdings, while larger
offers, IPOs underwritten by top-tier underwriters, and equity carve-outs are associated with greater post-
IPO ownership concentration. The results we report in Table 6 suggest that more widespread access to the
Internet may lead to greater oversight of management by outside blockholders. Thus, Internet penetration
is not only correlated with a lower cost of going public, but also may to play a positive role in firm-level
governance.
Conclusion
Prior research finds that the Internet has had a profound impact on markets for life insurance (Brown
and Goolsbee, 2002), automobiles (Zettelmeyer, Morton, and Silva-Risso, 2006), used books (Ghose,
Smith, and Telang, 2006), and airlines (Orlov, 2011). One of the many benefits of the Internet is reduced
information acquisition costs that result in less information asymmetry and fewer adverse selection
problems. Given the important roles that information asymmetry and adverse selection play in the capital
markets, we consider the impact of the Internet on IPO outcomes. Specifically, we study whether cross-
18
country variation in the rate of Internet penetration is related to offer price precision, initial returns, and
post-IPO ownership concentration.
Examining 9,432 IPOs issued in 34 countries from 1998 to 2008, we find that IPO firms tend to set
more precise offer prices and exhibit smaller initial returns in countries where more people have greater
access to information via the Internet. The results are robust to controls for newspaper circulation and
alternative measures of initial returns. This is consistent with the notion that greater Internet penetration is
associated with less information asymmetry among IPO participants. When we introduce country-level
measures of trust, we find that the negative relation between Internet penetration and underpricing is
driven by countries with high levels of trust. In addition, we find that ownership concentration is
positively correlated with Internet penetration at least one year after the IPO. This indicates that the
reduced information asymmetry brought about by greater Internet penetration motivates larger post-IPO
blockholdings.
Despite the widespread adoption of the Internet in most developed nations, access to the Internet is
not as common in many developing countries. For example, as of 2008 approximately one in three people
in Brazil had access to the Internet. Our results suggest that accessibility to the Internet can have a
positive impact on a country’s capital markets by reducing information asymmetry and decreasing the
cost of raising equity capital for companies seeking to go public.
19
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22
Fig. 1 Internet penetration by country – 1998 and 2008 Countries are reported alphabetically. Bar heights represent the number of internet users per 100 people by country in 1998 and 2008.
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Fig. 2 Number of IPOs and average underpricing by country Countries are reported alphabetically. Bar heights represent the number of IPOs issued in each country from 1998-2008. Line represents average IPO underpricing in each country during the same period.
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Fig. 3 Internet penetration and IPO underpricing Countries are sorted into terciles based on Internet penetration. Bar heights represent the average Internet penetration for the tercile. The line shows the average country-level underpricing by tercile.
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25
Table 1 – Descriptive statistics
N Average Std Dev Minimum Maximum Internet penetration 9,432 44.599 23.377 0.139 90.000 Newspaper circulation 9,432 2.931 2.378 0.345 15.091 Trust 8,145 0.372 0.101 0.028 0.680 Initial return 9,432 0.391 0.632 –0.360 3.862 Integer offer price 9,432 0.504 0.500 0.000 1.000 Top tier underwriter 9,432 0.247 0.431 0.000 1.000 Price stabilization 9,432 0.010 0.019 –0.074 0.125 IPO activity 9,432 0.027 0.018 0.001 0.092 Recent market return 9,432 0.029 0.109 –0.488 1.132 Stock market turnover 9,432 1.022 0.567 0.077 3.766 Antidirector rights index 9,432 3.806 1.232 0.000 5.000 Offer size 9,432 107.108 536.364 0.100 23844.340 Volatility 9,362 0.049 0.041 0.000 1.571 Bookbuilt 8,849 0.656 0.475 0.000 1.000 Firm commitment 9,356 0.545 0.498 0.000 1.000 Equity carveout 9,360 0.036 0.186 0.000 1.000 Bank ownership permitted 9,432 0.414 0.493 0.000 1.000 Hi tech firm 9,432 0.242 0.428 0.000 1.000
This table presents descriptive statistics for the entire sample of 9,432 IPOs. Internet penetration is the number of internet users per 100 people as reported by The World Bank. Newspaper circulation is total average circulation per 1,000 inhabitants as of 1997, based on data from the UNESCO Institute for Statistics. Trust is the percentage of respondents who answered that most people can be trusted when asked the following (The World Values Survey): “Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people?” Initial return is the first-day secondary market closing price divided by the final offer price, minus one. Integer offer price is an indicator variable set equal to one for IPOs priced on an integer, and zero otherwise. Top-tier underwriter is an indicator variable set to 1 for IPOs underwritten by an investment bank appearing in the top 25 of SDC’s league tables in the issue year, and zero otherwise. Price stabilization is the difference in the number of IPOs with initial returns between zero and one percent and the number of IPOs with initial returns between zero and negative one percent, divided by the total number of IPOs in each country. IPO activity is the ratio of the total number of IPOs in the issue year divided by the number of Datastream listed equities for the country of listing as of 2008. Recent market return is the return on the Datastream index for the country of listing over the three months preceding the offering. Stock market turnover equals the ratio of the total value of shares traded to aggregate market capitalization as reported annually by The World Bank. The antidirector rights index is a measure of the legal protection afforded to corporate shareholders (La Porta, Lopez-de-Silanes, and Shleifer, 1998). Offer size is the inflation-adjusted offer value in millions of U.S. dollars. Volatility is the standard deviation of stock returns measured over the calendar month following the IPO date. Indicator variables are set equal to one for bookbuilt, firm commitment, and equity carve-out deals. Bank ownership is a dummy variable set to one when bank ownership of nonfinancial firms is either unrestricted or permitted and zero if bank ownership is restricted or prohibited as reported in Barth, Caprio, and Levine (2006). Hi tech firm is an indicator variable set equal to one for firms in one of the hi-tech industries identified by Ljungqvist and Wilhelm (2003), and zero otherwise.
26
Table 2 – Likelihood of integer offer price
Model 1 Model 2 Model 3 Internet penetration –0.001*** –0.002*** Newspaper circulation 0.022*** 0.025*** Medium offer price 0.131*** 0.132*** 0.138*** High offer price 0.214*** 0.219*** 0.228*** Volatility 1.236*** 1.141*** 1.190*** Top tier underwriter 0.180*** 0.179*** 0.191*** IPO activity –5.905*** –4.545*** –5.387*** Stock market turnover 0.265*** 0.234*** 0.254*** Offer size (log) 0.017*** 0.016*** 0.008** Hi tech firm 0.092*** 0.083*** 0.089***
Pseudo R2 0.286 0.295 0.299 Number of observations 9,350 9,350 9,350
This table presents the marginal effects from logistic regressions examining the determinants of integer offer prices. The dependent variable is an indicator variable set equal to one for IPOs priced on an integer, and zero otherwise. Medium (high) offer price is an indicator variable set equal to one for IPOs priced at or above the 50th (75th) percentile, within country. All other variables are defined in the notes to Table 1. Regressions include issue year indicator variables. Respectively, ***, **, and * denote significance of the coefficient at the 1, 5, and 10 percent level.
27
Table 3 – IPO underpricing
Model 1 Model 2 Model 3 Intercept 0.454** 0.592** 0.496** Internet penetration –0.007** –0.007* Newspaper circulation –0.027 –0.016 Top tier underwriter 0.014 –0.028 0.014 Price stabilization 0.798 1.149 1.062 IPO activity 2.012* 1.786 1.800* Recent market return 0.957*** 1.063*** 0.959*** Stock market turnover 0.111 0.032 0.112 Antidirector rights index 0.022 –0.010 0.017 Offer size (log) –0.037* –0.012 –0.034* Integer offer price 0.027 0.008 0.037 Bookbuilt –0.122 –0.147 –0.117 Firm commitment –0.010 0.001 –0.013 Equity carveout –0.015 –0.058 –0.019 Bank ownership permitted –0.298** –0.313** –0.284** Hi tech firm 0.111* 0.065 0.109
R2 0.163 0.140 0.165 Number of observations 8,769 8,769 8,769
This table presents OLS regressions of IPO underpricing on country-level Internet penetration. The dependent variable is the IPO underpricing calculated as the secondary market closing price divided by the final offer price, minus one. All other variables are defined in the notes to Table 1. Regressions include industry indicators based on the industry classifications reported by Dyck and Zingales (2004) and issue year indicator variables. Respectively, ***, **, and * denote significance of the coefficient at the 1, 5, and 10 percent level based on standard errors clustered at the country level (Rogers, 1993).
28
Table 4 – IPO returns (one-calendar month)
Model 1 Model 2 Model 3 Intercept 0.413** 0.547** 0.438** Internet penetration –0.008** –0.008** Newspaper circulation –0.023 –0.010 Top tier underwriter 0.092 0.045 0.093 IPO activity 1.606 1.403 1.436 Recent market return 1.074*** 1.191*** 1.075*** Stock market turnover 0.111 0.022 0.113 Antidirector rights index 0.045** 0.011 0.043* Offer size (log) –0.046** –0.019 –0.043** Integer offer price 0.068 0.042 0.076 Bookbuilt –0.099 –0.127 –0.094 Firm commitment –0.070 –0.054 –0.072 Equity carveout –0.018 –0.065* –0.021 Bank ownership permitted –0.286** –0.307** –0.275** Hi tech firm 0.140* 0.088 0.138*
R2 0.123 0.104 0.124 Number of observations 8,758 8,758 8,758
This table presents OLS regressions of IPO underpricing on country-level Internet penetration. The dependent variable is the IPO return calculated as the secondary market closing price after 22 trading days divided by the final offer price, minus one. All other variables are defined in the notes to Table 1. Regressions include industry indicators based on the industry classifications reported by Dyck and Zingales (2004) and issue year indicator variables. Respectively, ***, **, and * denote significance of the coefficient at the 1, 5, and 10 percent level based on standard errors clustered at the country level (Rogers, 1993).
29
Table 5 – Trust
Continuous
Measure Above median
indicator Above 75th percentile
indicator Intercept –0.552** 0.151 0.308* Internet penetration 0.006** –0.006** –0.004** Trust 2.498*** 0.400* 0.616*** Internet penetration × Trust –0.038*** –0.004 –0.009*** Top tier underwriter 0.049 0.026 0.045 Price stabilization –1.099 –1.008 –0.195 IPO activity 1.560 2.267* 1.901* Recent market return 0.915*** 0.961*** 0.930*** Stock market turnover 0.107* 0.155** 0.110** Antidirector rights index 0.027 0.048* 0.013 Offer size (log) –0.060*** –0.048*** –0.059*** Integer offer price 0.098 0.053 0.092 Bookbuilt –0.035 –0.077 –0.039 Firm commitment –0.022 –0.040 –0.017 Equity carveout 0.011 –0.006 0.008 Bank ownership permitted –0.171*** –0.247*** –0.178* Hi tech firm 0.157** 0.152** 0.143**
R2 0.224 0.212 0.219 Number of observations 7,620 7,620 7,620
This table presents OLS regressions of IPO underpricing on country-level Internet penetration and country-level measures of trust. The measures of trust are based on the World Values Survey, which asks: “Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people?” Trust is defined in the first model as the percentage of respondents who answered that most people can be trusted. The second and third models use indicator variables for above median and above 75th percentile trust scores (in sample), respectively. The dependent variable is the IPO underpricing calculated as the secondary market closing price divided by the final offer price, minus one. All other variables are defined in the notes to Table 1. Regressions include industry indicators based on the industry classifications reported by Dyck and Zingales (2004) and issue year indicator variables. Respectively, ***, **, and * denote significance of the coefficient at the 1, 5, and 10 percent level based on standard errors clustered at the country level (Rogers, 1993).
30
Table 6 – Post-IPO ownership concentration
Ownership Herfindahl Outside blockholdings 6 months 1 year 2 years 6 months 1 year 2 years Intercept –8.227*** –7.187*** –4.556** –7.114*** –6.097** –3.104 Internet penetration 0.060** 0.047* 0.035 0.062** 0.043* 0.029 Initial return –0.254* –0.176 –0.140 0.009 0.017 –0.246** Offer size (log) –0.092 0.134* 0.299*** –0.025 0.264** 0.421*** Top tier underwriter 0.525* 0.798** 0.758** 0.982*** 0.972*** 0.960** Stock market turnover –0.097 0.025 –0.438 –0.055 0.097 –0.453 Underdevelopment index 0.853 –0.822 –3.098 –2.962 –4.481 –7.446 Equity carveout 1.306** 1.351** 1.256** 0.999* 1.204* 1.270** Government –0.555 –0.326 –0.502 –0.287 –0.222 –0.169 Employee/family ownership 8.270*** 8.131*** 7.726*** –3.618*** –3.636*** –4.040***
R2 0.361 0.334 0.344 0.152 0.171 0.199 Number of observations 2,931 3,985 5,421 2,931 3,985 5,418
This table presents OLS regressions of post-IPO ownership on initial returns. The dependent variable in the first three regressions is the log of the ratio of the ownership Herfindahl index to 1 minus the ownership Herfindahl index. The ownership Herfindahl index is the sum of the squared fractional ownership of government, cross holdings, pension funds, investment companies, employee and family, foreign holdings, and others, as reported by Datastream. The dependent variable in the last three regressions is the log of the ratio of outside blockholdings to 1 minus the outside blockholdings. Outside blockholdings is the percentage of shares held in blocks of 5% or more minus employee and family holdings, as reported by Datastream. Each measure is calculated 6 months, 1 year, and 2 years after the IPO issue date. Internet penetration is the number of internet users per 100 people, as reported by The World Bank. Initial return is measured as the secondary market closing price divided by the final offer price, minus one. Offer size is the natural log of the CPI-adjusted offer value in millions of U.S. dollars. Top-tier is an indicator variable set to 1 for IPOs underwritten by an investment bank appearing in the top 25 of SDC’s league tables in the issue year, and zero otherwise. Stock market turnover is reported annually by The World Bank. Underdevelopment is a multidimensional development index from Butler and Fauver (2006) that includes the following five dimensions of development: workforce deployment, health, education, technological infrastructure, and transportation infrastructure. Indicator variables are set equal to one for equity carve-out deals and government owned companies. Employee/family ownership is the percentage of shares held by employee and family members, as reported by Datastream. Regressions include IPO year and industry dummies. Industry classifications reflect those reported by Dyck and Zingales (2004). Respectively, ***, **, and * denote significance of the coefficient at the 1, 5, and 10 percent level.
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