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The Impact of International Financial Reporting Standards
on Comparability: A Test using IPO Underpricing

Jangwon Suh
University of Massachusetts, Dartmouth
Donal Byard
Masako Darrough
Baruch College – The City University of New York
April 2015

ABSTRACT
Using a sample of IPO firms from countries that mandated IFRS adoption in 2005, we compare IPO
underpricing for firms that went public after 2005 using IFRS with that of matched IPOs that went public
prior to 2005 using domestic GAAP. While mandatory IFRS adoption increases the number of listed
industry peers that report in the same accounting standards (i.e., potentially comparable firms), we find
that only those IFRS-reporting industry peers listed in jurisdictions with high-quality enforcement
environments are associated with a reduction in IPO underpricing: only peer firms based in high quality
enforcement jurisdictions provide enhanced comparability. Further, in the pre-2005 period, we find that
IPOs that voluntarily adopt IFRS also experience a reduction in IPO underpricing via enhanced
comparability. Our results highlight that IFRS adoption can generate a positive externality by enhancing
comparability, but only when coupled with high-quality enforcement (or strong firm-level reporting
incentives).

Keywords: International Financial Reporting Standards (IFRS); IPO underpricing;
comparability; enforcement

I. INTRODUCTION
We examine if the adoption of International Financial Reporting Standards (IFRS)
increases comparability. By greatly increasing the number of potentially comparable firms, IFRS
adoption is likely to increase comparability that will benefit investors (see McCreevy 2005).
Comparability is the “quality of information that enables users to identify similarities in and
differences between two sets of economic phenomena” (Financial Accounting Standards Board,
1980). Using initial public offering (IPO) underpricing as a setting, we test whether investors
benefit from enhanced comparability under IFRS compared to domestic generally accepted
accounting principles (GAAP). Further, focusing on the quality of countries’ enforcement
environments, we examine if all of the potentially comparable firms available under IFRS
actually contribute to providing enhanced comparability.
IPO underpricing refers to the phenomenon whereby the offer prices of the newly issued
shares of firms going public tend to be lower than their first trading-day closing prices.1 IPO
underpricing has been attributed to information asymmetry among participants in the IPO
process regarding the value of an IPO firm (Rock 1986; Beatty and Ritter 1986; Benveniste and
Spindt 1989), and has been documented throughout the world (Loughran, Ritter, and Rydqvist
1994). Information asymmetry about firm value is particularly high before a firm goes public. To
value IPO firms, investors typically use comparison measures such as industry peers’ priceearnings ratios. 2 By using IFRS, an IPO firm can generate a greater number of potentially
comparable firms throughout the world. IFRS may therefore enable investors to extract more
                                                            
1

Following prior studies, we measure the degree of IPO underpricing by the first trading-day closing price relative
to the offer price. For example, when LinkedIn went public on May 19, 2011, the offer price and closing price were
$45 and $94.25, respectively, giving underpricing of 109% (= $94.25/$45 – 1).
2
For example, in its Form S-1 registration statement filed with the Securities and Exchange Commission (SEC),
Groupon, which went public on November 4, 2011, observed that “among the factors to be considered in
determining the initial public offering price will be …. the price-earnings ratios, price-sales ratios, market prices of
securities, and certain financial and operating information of companies engaged in activities similar to ours”
(Groupon 2011, p. 135, emphasis added).

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useful information by clarifying commonalities and differences among a much larger number of
industry peers. Such a potential increase in the overall level of comparability (i.e., enhanced
comparability) may reduce IPO underpricing by reducing investors’ uncertainty and information
asymmetry about IPO firms. 3 The global IPO market therefore provides an ideal setting to
examine the effects of IFRS on comparability. Broadly speaking, there are two settings: (1)
countries that mandated domestic GAAP reporting prior to 2005 but mandated IFRS from 2005
onward; and (2) countries that allowed voluntary IFRS adoption prior to 2005 but mandated
IFRS from 2005 onward. We use both settings to examine whether the potential for enhanced
comparability under IFRS is associated with a reduction in IPO underpricing.
The adoption of IFRS may change IPO underpricing via two potential channels: (1) a
change in IPO firms' reporting quality, and (2) an increase in the overall level of comparability
for investors. Hong, Hung, and Lobo (2014) provide evidence regarding the first channel: they
find that IPO firms based in countries with a larger number of accounting changes (from
domestic GAAP to IFRS) and stronger “implementation credibility” (i.e., stronger enforcement)
in their home countries experience a greater decrease in IPO underpricing following mandatory
IFRS adoption. In contrast, our study focuses on the role of comparability under IFRS in
mitigating IPO underpricing. By focusing on the second channel, our analysis extends and
complements that of Hong et al. (2014).
This paper first tests if enhanced comparability under mandatory IFRS adoption reduces
IPO underpricing. Following DeFond, Hu, Hung, and Li (2011), we use listed industry peers that
report in the same accounting standards as an IPO firm as a proxy for “comparable firms.” While
mandatory IFRS adoption will obviously increase the number of potentially comparable firms, it
                                                            
3

We use the term “overall comparability” to denote the totality of all comparability arising from comparable firms
(proxied by all listed industry peers using the same accounting standards), as opposed to the marginal effect from
one additional comparable firm.  

2
 
 

 

may also adversely impact the level of comparability per listed peer. This is because IFRSreporting comparable firms are by definition based in different countries, which might have
different operating, regulatory, cultural, and institutional environments. As a result, it is not a
foregone conclusion that IFRS will lead to an increase in overall comparability that will benefit
investors (by reducing IPO underpricing).
While IFRS will unambiguously increase the number of potentially comparable firms, not
all of these firms may provide genuine comparability that benefits investors. The financial
information of some peer firms may be unreliable. Prior studies identify the quality of countries’
enforcement environments as a key determinant of firms’ compliance with accounting standards.
As our second question, we test if the quality of countries’ enforcement environments affects
comparability under IFRS. Specifically, we test if the quality of the enforcement environments in
the countries where potentially comparable firms are domiciled affects comparability under
IFRS. This is a central focus of our paper. While it is widely acknowledged that any increase in
overall comparability from mandatory IFRS adoption is likely to depend on whether IFRS are
effectively and consistently enforced across jurisdictions (e.g., McCreevy 2005), to the best of
our knowledge, our study provides the first direct evidence of this possible positive externality
(enhanced comparability) arising from high-quality enforcement.
For our analysis of mandatory IFRS adoption, our test sample consists of IPO firms from
countries that mandated domestic GAAP prior to 2005 but IFRS after 2005. Our focus is on the
treatment IPO firms that went public using IFRS after 2005 (specifically, in 2006 and 2007).4
We compare these IFRS-reporting IPO firms with benchmark IPO firms that went public using
domestic-GAAP prior to 2005 (specifically, in 2003 and 2004). We match our treatment firms
with our benchmark firms by industry, country, and IPO proceeds. Thus, our mandatory IFRS
                                                            
4

 We focus our analysis on IPOs before the financial crisis period. 

3
 
 

 

adoption test sample consists of a matched-pair sample of IPO firms reporting in IFRS (in the
post-period) and domestic GAAP (in the pre-period); this controls for country-level institutional
factors that may affect IPO underpricing.5 Using this matched-pairs sample, we first test if the
increase in the total number of potentially comparable firms following mandatory IFRS adoption
is associated with a decrease in IPO underpricing, i.e., whether there is enhanced comparability
under IFRS. We then test if enhanced comparability under IFRS is associated with the quality of
the enforcement environments of the countries where the listed industry peers are domiciled.
For our analysis of the effects of mandatory IFRS adoption, we use both: (1) change
models using the mandatory adoption test sample of matched pairs of IPOs (based in countries
that mandated IFRS adoption in 2005) outlined above; and (2) difference-in-differences (DID)
models using both the mandatory adoption test sample and a control sample. The control sample
consists of a similar matched-pair sample of IPOs drawn from countries that did not mandate the
adoption of IFRS over our sample period. We find consistent results using both sets of tests.
Specifically, we find that only IFRS-reporting industry peers domiciled in strong enforcement
jurisdictions are associated with a decrease in IPO underpricing following mandatory IFRS
adoption. Industry peers domiciled in weak enforcement jurisdictions do not appear to provide
genuine comparability that benefits investors. These results are robust to various alternative
specifications, including the EU’s adoption of the Prospectus Directive, a concurrent regulatory
change (Christensen, Hail, and Leuz 2013, 2014).

                                                            
5

We exclude two groups of IPO firms from this comparison. First, some countries (e.g., Germany) permitted
voluntary IFRS adoption prior to 2005. We exclude these voluntary IFRS adopters from our mandatory adoption test
sample, but include them in our voluntary adoption sample (see Section V below). Second, the EU-wide mandatory
adoption of IFRS in 2005 applied only to public companies listed on “EU regulated” exchanges (e.g., London Stock
Exchange in the UK). Secondary exchanges―or “exchange-regulated” markets―such as AIM (UK), Alternext
(Continental Europe), FirstNorth (Scandinavia), and Marche Libre (France) were not required to mandate the
adoption of IFRS in 2005, so we exclude listings on these exchanges from our mandatory adoption test sample.  

4

 
 

 

For our second set of analyses, we examine voluntary IFRS adoption in the pre-2005
period, and find that: (1) voluntary IFRS adopters are more likely to choose to report in IFRS
when they have relatively fewer comparable firms reporting in domestic GAAP; and (2)
controlling for self-selection, there is enhanced comparability following voluntary IFRS adoption
that is associated with a reduction in IPO underpricing.
This paper makes a number of contributions to several strands of literature regarding the
effects of both voluntary and mandatory IFRS adoption, as well as IPO underpricing. We show
that IPO underpricing is affected by enhanced comparability following mandatory IFRS adoption.
Our results also show that the quality of the enforcement environments where potentially
comparable firms are domiciled plays a key role in determining the level of comparability under
mandatory IFRS adoption. Thus, our results highlight that rigorous implementation/enforcement
is critical in generating the positive externality of enhanced overall comparability under IFRS.
For voluntary IFRS adoption, our results suggest that comparability is both a factor in firms’
choice of accounting standards, and a benefit of voluntary IFRS adoption. Finally, our results
provide new evidence that accounting comparability affects IPO underpricing. These results may
be of interest to regulators and policymakers.
The remainder of this paper is organized as follows. Section II reviews the prior literature
and develops our hypotheses regarding mandatory IFRS adoption. Sections III and IV outline our
study design, sample selection, and results related to mandatory IFRS adoption. Section V
presents our second set of analyses of voluntary IFRS adoption. Additional analysis and
robustness are reported in Section VI, while Section VII concludes.

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II. PRIOR STUDIES AND HYPOTHESES
IPO Underpricing
Theoretical studies attribute IPO underpricing to uncertainty about firm value and the
associated information asymmetry among the participants in the IPO market (Rock 1986; Beatty
and Ritter 1986; Benveniste and Spindt 1989). Prior to an IPO, investors in public capital
markets have access to only limited financial information about the firm, and therefore IPO firms
are subject to a heightened level of information asymmetry. Underpricing is a mechanism to
attract (or retain) asymmetrically informed investors to the IPO market. It might also incentivize
investment bankers to exert effort in the underwriting process. If IFRS provide investors with
more useful information than domestic GAAP, then IPO firms using IFRS may have a lower
level of IPO underpricing. As discussed earlier, IFRS may provide investors with more useful
information than domestic GAAP through two channels: (1) potentially higher reporting quality;
and (2) greater overall comparability. We examine the second channel, i.e., how IFRS may
reduce IPO underpricing via enhanced overall comparability.
Mandatory IFRS Adoption and Comparability
Mandatory IFRS adoption can affect overall comparability through two effects. First,
when a firm goes public in the post-mandatory IFRS adoption period, it will (1) automatically
acquire a greater number of potentially comparable firms: its industry peers in its home country
plus IFRS-using industry peers throughout the world. While the number of industry peers
reporting in the same accounting standards will increase, it is possible that (2) comparability per
industry peer could be lower for IFRS than for domestic GAAP. We expect that the first effect of
the far greater number of comparable firm will dominate (see below) the second effect, resulting

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in enhanced overall comparability and a reduction in IPO underpricing under mandatory IFRS
adoption. Our first hypothesis, stated in the alternative form, is:
H1: Following mandatory IFRS adoption, enhanced overall comparability under IFRS
will reduce IPO underpricing relative to that under domestic GAAP.
It is possible, however, that the increased number of comparable firms under IFRS do not
provide genuine comparability that benefits investors, with the result that IFRS adoption does not
lead to enhanced overall comparability. While effect (1) is straightforward, effect (2) is not. The
average level of comparability per listed industry peer might be lower for IFRS than for domestic
GAAP, partially due to the fact that IFRS may not be consistently interpreted and enforced
across countries.6 Furthermore, as a more principles-based set of standards, IFRS may be more
open to interpretation and managerial discretion (Ahmed, Neel, and Wang 2010). Thus, industry
peer firms from outside the IPO firm’s home country may not provide genuine comparability.
However, an IPO firm has, at a minimum, the same number of comparable firms in its home
country before and after mandatory IFRS adoption. These domestic listed peers (now reporting
in IFRS rather than domestic GAAP) will still be subject to the same firm-level reporting
incentives and are in the same enforcement environment. As a result, it is unlikely that the
overall effect on comparability from the two effects could be negative, so our alternative
hypothesis is that mandatory IFRS adoption will cause no change in overall comparability.
Evidence so far is mixed on whether or not IFRS provide greater overall comparability
than domestic GAAP. On the one hand, consistent with enhanced comparability following IFRS
                                                            
6

Variation in institutions across countries may cause variation in firm-level reporting incentives (Leuz, Nanda, and
Wysocki 2003; Ball 2006; Cascino and Gassen 2015), with the result that IFRS may be applied differently across
countries. Firm-level reporting incentives are shaped by country-level institutions such as enforcement quality (Leuz
et al. 2003; Ball 2006) and investor protection (Djankov, LaPorta, Lopez-de-Silanes, and Shleifer 2008). As a result,
firms' incentives to rigorously implement the requirement of IFRS are likely to vary across countries, possibly
leading to lower per firm comparability. In addition, the process whereby different jurisdictions "endorse" IFRS for
use in these jurisdictions creates the possibility of carve-ins and carve-outs, potentially leading to the use of different
versions of IFRS across different countries.

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adoption, prior studies document that: foreign mutual fund ownership increases with the increase
in the number of listed industry peers (DeFond et al. 2011); there is an increase in transnational
information transfer (Yip and Young 2012; Wang 2014); and, consistent with enhanced
comparability, there is an improvement in the information environment of UK firms (Brochet et
al. 2013). On the other hand, Lang et al. (2010) find no evidence that mandatory IFRS adoption
increases accounting comparability. 7 Using a similar approach, Cassino and Gassen (2014)
conclude that the overall impact of mandatory IFRS adoption on comparability is only marginal.
Comparability under IFRS: The Role of Enforcement
The quality of enforcement environments is critical in determining firms’ actual reporting
practices (Ball 2006; Ball, Kothari, and Robin 2000; Ball, Robin, and Wu 2003). Strong
enforcement requires enhanced auditing and regulation, thereby limiting managers’ exercise of
discretion and opportunism (Leuz et al. 2003). Consistent with this argument, prior studies show
that the capital market benefits (e.g., increased liquidity, decreased cost of capital, and more
accurate analyst forecasts) associated with mandatory IFRS adoption are concentrated among
firms domiciled in stronger enforcement environments (Daske et al. 2008; Li 2010; Byard, Li,
and Yu 2011). The results of these studies are consistent with the idea that the quality of the
enforcement environment where mandatory IFRS adopting firms are domiciled is critical in
determining how mandatory IFRS adoption affects these firms' reporting quality.
We hypothesize that the quality of enforcement environments is also likely to affect the
level of comparability under IFRS. However, our hypothesis is about the quality of the
enforcement environments of the countries where an IPO firm’s potentially comparable firms are
domiciled, not where an IPO firm itself is listed. While IFRS provides a far greater number of
                                                            
7

 They employ a measure of accounting comparability developed by De Franco, Kothari, and Verdi (2011), which is
based on how closely the earnings of two firms represent the same economic events captured by stock returns 

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potentially comparable firms than domestic GAAP, this will only lead to enhanced comparability
if these listed industry peers faithfully and consistently implement IFRS (McCreevy 2005). The
quality of the enforcement environments of the jurisdictions where an IPO firm’s industry peers
are domiciled will determine whether or not these industry peers faithfully and consistently
implement IFRS.8 Our second hypothesis therefore examines how the quality of the enforcement
environments of the countries where an IPO firm’s listed peers are domiciled affects the degree
to which these listed peers enhance overall comparability and, thus, affect IPO underpricing.
Stated in the alternative form, our second hypothesis is:
H2: Following mandatory IFRS adoption, only those listed industry peers domiciled in
high quality enforcement jurisdictions have an effect in reducing IPO underpricing.
III. STUDY DESIGN AND SAMPLE SELECTION
The Institutional Setting
The institutional setting of the global IPO market is complex, posing a number of
challenges for our study. First, the mandatory EU-wide adoption of IFRS in 2005 applied only to
firms filing consolidated financial statements that were listed on “EU regulated” exchanges (the
primary exchanges in each country). Firms listed on secondary exchanges (e.g., the AIM market
in London)―also known as “exchange-regulated” markets―were not subject to mandatory IFRS
adoption in 2005.9 Second, different countries had different regulatory policies with respect to
IFRS prior to 2005. For example, while the UK and Sweden forbade the use of IFRS for
domestic listed firms, Germany allowed voluntary IFRS adoption. Third, we can only observe a
                                                            
8

For example, if an IFRS-reporting IPO's listed industry peers are all located in countries with poor enforcement
environments, then on average these peer firms will not have incentives to faithfully and consistently apply IFRS. So
it is unlikely that they will provide genuine comparability for the IPO firm. In the absence of strong enforcement
environments, industry peers are unlikely to have incentives to credibly implement IFRS (Daske, Hail, Leuz and
Verdi 2008) and may merely adopt IFRS "as a label" (Daske, Hail, Leuz, and Verdi 2013).
9
While these exchange-regulated markets did not have to adopt IFRS in 2005, they could choose to do so later. See
Vismara, Paleari and Ritter (2012) for a discussion of Europe’s “exchange-regulated” secondary markets.

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firm going public once in its life, so we can’t use a firm as its own control. Lastly, since we are
using a global sample of international IPOs, we need to be cognizant of the fact that important
country-level institutional differences (e.g., investor protection) may affect the IPO process, and
hence the degree of IPO underpricing, differently in different countries.
Study Design: Identifying the Effect of Mandatory IFRS Adoption on IPO Underpricing
A number of countries mandated IFRS adoption in 2005. Our mandatory adoption test
sample consists of IPOs from these countries over the period 2003 through 2007, and consists of
a matched-pair sample with: (1) a treatment group of IPOs that went public in 2006 and 2007
using IFRS, and (2) a matched benchmark group of IPOs that went public using domestic GAAP
in 2003 and 2004. We exclude 2005, the transition year, from our sample. 10 We match the
treatment and benchmark IPO firms one-to-one by country, industry, and closest proceeds, with
replacement.
For our first set of analyses we estimate two change models using this (matched-pairs)
test sample. A change model is estimated using the differences between each matched pair: the
treatment (IFRS-reporting) IPO vs. the benchmark (domestic GAAP-reporting) IPO. A change
model can be specified as a fixed effects model with a dummy variable for each matched pair (so
the model is estimated using only the variation within pairs). Thus, we test H1 using the
following model:
IniRet = X’β + β1 IFRS + β2 log(1+Comp) + β3 IFRS×log(1+Comp) + Controls + υ

(1a)

where IniRet is our measure of IPO underpricing and is calculated as the first trading-day return;
X is a matrix of 493 dummy variables, one for each pair of matched observations (see sample
below). Within each matched pair of IPOs, another dummy variable IFRS is coded one (zero) for
                                                            
10

Nevertheless, our results are robust to including observations from 2005 in our sample.

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the IFRS- (domestic GAAP-) reporting IPO in the pair. log(1+Comp) is the natural log of one
plus Comp, the number of comparable firms. For a domestic GAAP-reporting IPO, Comp is the
number of domestic GAAP-reporting industry peers; for an IFRS-reporting IPO, Comp is the
number of worldwide industry peers reporting in IFRS. We use Fama and French's (1997)
industry classification to identify a firm’s industry peers. The control variables are a set of
controls for IPO characteristics (e.g., proceeds size, cross listing, etc.) which are explained in
Section IV below (see also the endnotes of Table 3).
Using a matched pair sample (matched by country and industry) with fixed effects for
each pair of matched observations (X above) is equivalent to including both country and industry
fixed effects. The model therefore controls for variation in the intercept arising from variation in
country-level institutional characteristics such as investor protection (Djankov et al. 2008) and
enforcement quality (Kaufmann, Kraay, and Mastruzzi 2007) in IPO firms’ home countries.11
This is important since variation in country-level institutional characteristics may: (1) have a
direct impact on the level of IPO underpricing (Boulton, Smart, and Zutter 2010), and (2) affect
IPO firms’ reporting incentives and, hence, reporting quality (Leuz et al. 2003). However, while
matching in this way provides a control for country-level institutional variation and industry
effects, it results in a smaller sample size, 12 potentially affecting the generalizability of our
results.
Interpreting the coefficient on the IFRS variable, β1, is problematic, however. Given the
matched pair design with fixed effects for matched pairs, it is clear that β1 picks-up the average
                                                            
11

 This also controls for industry-wide risk factors that affect investor uncertainty, which may determine IPO
underpricing (Ritter 1984). 
12
IFRS-reporting IPO firms that are not matched with domestic GAAP-reporting IPO firms (by country and by
industry) are eliminated from the sample. This matching substantially reduces the sample size. However, the
matching balances the sample with respect to the country and industry composition of the IFRS- and domestic
GAAP-reporting IPO firms in the sample.

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effect of variation in reporting quality between the matched domestic GAAP and IFRS-reporting
firms in each pair. Nevertheless, it is critical to realize that the paired firms are from different
time periods: the domestic GAAP (IFRS) IPOs are from 2003-2004 (2006-2007), so the "IFRS"
dummy variable is also a time period variable. It is well known that IPO markets go through
"hot" and "cold" period cycles (e.g., Helwege and Liang 2004; Ljungqvist, Nanda and Singh
2006; Yung, Colak and Wang 2008). Such time period shocks will be reflected in β1; the effects
of any macro-economic shocks―which will, of course, vary by time―will also be reflected in β1.
These time period effects render any interpretation of β1 as a measure of the effect of differences
in reporting quality arising from mandatory IFRS adoption problematic.
Equation (1a) is used to test H1. Because IFRS typically allow for a far greater number of
potentially comparable firms than domestic GAAP, H1 predicts that IPO underpricing decreases
with the increase in overall comparability under IFRS. For any set of standards, since the
marginal effect is likely to decline as the total number of comparable firms increases, we use a
logarithmic transformation of Comp. The coefficients β2 and β3 approximate the incremental
effect on IPO underpricing of additional comparable firms. More specifically, β2 approximates
how a 1% increase in the number of comparable firms affects the degree of IPO underpricing for
a domestic GAAP-reporting IPO; β3 approximates how the effect of a 1% increase in the number
of comparable firms on IPO underpricing changes following mandatory IFRS adoption. H1
therefore predicts that β3 < 0.
Note, we are interested in estimating the effect on IPO underpricing of overall
comparability in either domestic GAAP or IFRS. Thus, we interpret β2.log(1+Comp) and
β2.log(1+Comp) + β3.IFRS×log(1+Comp) as estimates of the impact on IPO underpricing of the
level of overall comparability in domestic GAAP and IFRS.
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To test H2 we modify Equation (1a) to accommodate variation in the quality of the
enforcement environments of the countries where an IPO firm’s listed industry peers are
domiciled. To measure the quality of countries’ enforcement environments, we follow the prior
literature (e.g., Daske et al. 2008) and use the 2005 values of the “Rule of Law” index developed
by Kaufmann et al. (2007). If a country’s Rule of Law index is greater (less) than the median
value across all countries (0.74), then this country is classified as a strong (weak) enforcement
jurisdiction. We find consistent results using Transparency International’s Corruption Perception
Index.13
To differentiate between the level of enforcement of the countries where an IPO firm’s
potentially comparable firms are domiciled, we partition Comp into CompWeak and CompStrong and
test H2 using the following model:
IniRet = X’β + β1 IFRS + β4 log(1+CompWeak) + β5 log(1+CompStrong /(1+CompWeak))
+ β6 IFRS×log(1+CompWeak) + β7 IFRS×log(1+CompStrong /(1+CompWeak))
+ Controls + υ
.

(1b)

As in Equation (1a), X is a matrix of 493 dummy variables, one for each pair of matched IPOs.
In partitioning Comp into CompStrong and CompWeak, we normalize (1+CompStrong) by
(1+CompWeak) to ensure that Equation (1b) is nested within Equation (1a).14 This allows for the
comparability of results across models. For a domestic GAAP-reporting firm, all of its
comparable firms are domiciled in the same country. Thus, for  a domestic GAAP-reporting firm
                                                            
13

Several other indices have been proposed that measure different aspects of countries' legal systems such as the
level of creditor rights or investor protection. In the context of our study, we use the “Rule of Law” index from
Kaufmann et al. (2007) as a proxy for the overall institutional quality of a country that ensures compliance with laws,
rules, and, in particular, accounting standards. Since we are interested in the overall quality of the institutional
environment of a country as it pertains to the enforcement of all rules and laws, we believe the measures by
Kaufmann et al. (or the Corruption Perception Index of Transparency International) are the best proxy for the overall
quality of the institutions rather than a more limited index that focuses on just the enforcement of creditor right or
the level of investor protection.
14
 This follows from: log(1+Comp)=log(1+CompStrong+CompWeak)=log(1+CompWeak) (1+CompStrong / (1+CompWeak))
= log (1+CompWeak) + log(1+CompStong / (1+CompWeak)).  

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domiciled in a weak (strong) country, β4 (β5) approximates how a 1% increase in the number of
comparable firms (domiciled in the same country as the IPO firm) affects the degree of IPO
underpricing. For an IFRS-reporting IPO, β6 (β7) approximates how a 1% increase in the number
of comparable firms domiciled in weak (strong) enforcement countries affects the degree of IPO
underpricing, incremental to β4 (β5). For an IFRS-reporting IPO, comparability is potentially
provided by all IFRS-reporting listed industry peers, which can be located in either weak or
strong enforcement jurisdictions. Recall that H2 predicts that only those listed peers domiciled in
strong enforcement jurisdictions will provide genuine comparability for IFRS-reporting IPOs,
resulting in an increase in overall comparability under IFRS compared to that under domestic
GAAP; therefore H2 predicts that β7 < 0.
Difference-in-Differences
Our mandatory adoption test sample consists of 493 matched pairs of IPOs: each pair
consists of a treatment IPO firm that reports in IFRS (from 2006 to 2007) and a matched
benchmark IPO firm that reports in domestic GAAP (from 2003 to 2004). Using this sample, we
estimate Equations (1a) and (1b), both of which are change models. As already discussed, any
time-period specific shocks that affect the IPO market (e.g., IPO hot/cold period cycles, or
macroeconomic shocks) and IPO underpricing will be correlated with the treatment effect (i.e.,
the IFRS dummy variable) in our estimates of Equations (1a) and (1b).
One way to try to control for such time-period shocks is to use a control sample and a
Difference-in-Differences (DID) specification. However, since mandatory IFRS adoption applies
to all firms in a given country, and firms only go IPO once in their life, we cannot use a control
sample of IPO firms from the same countries as the test firms. Therefore, by necessity, we use a
control sample of non-IFRS-using IPOs from countries that did not mandate IFRS adoption over
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our sample period. Similar to the test sample, the control sample also consists of matched pairs
of IPO firms (matched by industry, country, and closest proceeds size, with replacement), one
from the period 2003 to 2004, and the other from the period 2006 to 2007. Only IPO firms in the
same industries as our mandatory adoption test sample firms are included in the control sample.
For our DID estimates, we use a dummy variable to distinguish between the test and control
samples; this dummy variable is interacted with each variable shown in Equation (1a) and (1b).
Note, to control for the effect of time period shocks, the DID specification assumes that
the test and control samples are similarly exposed to any (time period) shocks that are
uncorrelated with the treatment effect.15 However, in our setting the test and control samples are,
by necessity, drawn from different countries. If IPO market hot and cold periods are not perfectly
synchronized across countries, or if our test and control firms are subject to different
macroeconomic shocks, then there may be residual time period effects.16 The average effect of
any such time period shocks that are not perfectly identical across the test and control samples
will be reflected in the difference in β1 across the two samples. Therefore, as in our change
models, it is also problematic to interpret the difference in β1 across the test and control samples
in our DID model estimates as a measure of the effect of changes in reporting quality arising
from mandatory IFRS adoption.
Sample Selection

                                                            
15

This is the so called “parallel” assumption of the DID specification. It is assumed that, in the absence of the
treatment effect, the test and control samples would have moved in parallel―because they are equally exposed to
other uncorrelated shocks (see Abadie 2005).
16
It seems likely that hot and cold IPO markets are not perfectly synchronized across all countries. International
capital markets are, to some degree, segmented between countries―as evidenced by the widespread prevalence of
home bias (see Karolyi and Stulz, 2003; Ahearne, Griever, and Warnock 2004). Such capital market segmentation
between countries means that it is unlikely that hot and cold IPO markets are perfectly synchronized across all
countries.

15
 
 

 

Panel A of Table 1 describes the selection of the mandatory adoption (test and control)
samples; Panel B describes the selection of the voluntary adoption sample (discussed in Section
V below). For the mandatory adoption test sample, we first use the Security Data Corporation
(SDC) database to select a global sample of IPOs over the period 2006 to 2007. To avoid the
effects of the global financial crisis, we end our sample period in 2007. We retain only
observations for ordinary common shares. If there are multiple observations for the same firm on
the same day, then only one observation is used. This yields an initial global sample of 3,380
IPOs. We delete observations that are missing critical data, such as first day returns or
accounting standards. Accounting standards data are from Datastream or Compustat Global.17
We also delete IPOs in countries that did not mandate the adoption of IFRS in 2005 and IPOs on
secondary exchanges (e.g., AIM in UK), which still allowed the use of domestic GAAP for some
time after 2005. 18 This gives a sample of 749 test IPOs in 2006-2007 from countries that
mandated the adoption of IFRS in 2005. We then match these IFRS-reporting IPOs, one-to-one
(by industry, country, and proceeds size with replacement), with benchmark IPOs that went
public using domestic GAAP in 2003 and 2004. While we are able to match 493 IFRS and
domestic GAAP-reporting IPOs in this manner, we are unable to match the remaining 256 IFRSreporting IPOs. Our final mandatory adoption test sample thus consists of 493 matched-pairs of
IPOs (in total, 986 IPOs). Because of differences in sample selection procedures, our mandatory
adoption test sample is quite different from that of Hong et al. (2014); for example, they do not
match firms across the pre- and post-IFRS adoption periods.
                                                            
17

We use data for accounting standards from Compustat only when this data item is unavailable from Datastream.
In classifying Datastream and Compustat Global data on firm’s accounting standards between domestic GAAP and
IFRS we follow Table A1 of Daske et al. (2013).
18
Since firms on the AIM market in the UK were not required to adopt IFRS until 2007, we drop 2006 listings on
AIM. Of the 284 IPOs listed on AIM in 2005 and 2006, 163 reported using domestic GAAP. The other secondary
European exchanges that are identified in the SDC database are: Alternext, FirstNorth, and Marche Libre.

16
 
 

 

< Insert Table 1 about Here >
For our DID tests, we construct a control sample using the same procedures and sample
period, but drawing IPOs from countries that did not mandate the adoption of IFRS over our
sample period. Our control sample consists of 628 matched pairs of IPOs (1,256 IPO firms) from
the periods 2003 to 2004 and 2006 to 2007. Panel A of Table 2 shows the country distribution of
our mandatory adoption test and control samples; Panel B shows the country distribution of the
voluntary adoption sample (again, discussed in Section V below). Panel A shows that Australian
firms constitutes about 68-percent (672 of the 986 firms) of the mandatory adoption test sample.
As a robustness check, we exclude Australian firms from our sample and find that our inferences
are unchanged (see Section VI below). Panel A also shows that the largest number of control
firms is from the US.
< Insert Table 2 about Here >
IV. RESULTS
Descriptive Statistics
Table 3 provides descriptive statistics for the mandatory adoption test sample of 493
matched-pairs of IPOs: Panel A (B) shows data for the 493 IFRS-reporting (domestic GAAP)
IPOs. We winsorize the data at the 2% and 98% levels. Consistent with prior studies (e.g.
Loughran et al. 1994; Boulton et al. 2011), mean IniRet, the degree of IPO underpricing, is 23.9%
(20.1%) for IFRS- (domestic GAAP-) reporting IPOs. The number of potentially comparable
firms increased under IFRS: mean Comp, the raw number of listed industry peers using the same
accounting standards is 182.8 (32.3) for IFRS- (domestic GAAP-) reporting IPOs. For IFRS,

17
 
 

 

Comp equals the total number of listed industry peers using IFRS around the world.19 However,
for IFRS-reporting IPOs, not all comparable firms are domiciled in strong-enforcement
jurisdictions: mean CompStrong (CompWeak) is 146.8 (36.6). We use Fama and French’s (1997)
industry classification.
< Insert Table 3 about Here >
Table 3 also provides data for our control variables. While our matched-pairs design
controls for country and industry effects, there could still be differences at the firm level between
the two matched IPOs. Hence, we include controls for important IPO firm characteristics.
Proceeds is the IPO proceeds size expressed in millions of U.S. dollars (Habib and Ljungqvist,
1998), adjusted by the U.S. Consumer Price Index. The degree of Partial Adjustment indicates
the market’s interest in an IPO. Hanley (1993) shows that partial adjustment, the deviation of the
final offer price from the initial offer price range, is positively associated with the degree of
underpricing; Cross Listing equals one when an IPO firm lists in a foreign country, and zero
otherwise. Following Cliff and Denis (2004), we include Market Return, Market Volatility, and
#IPO to control for market sentiment. Market Return is the mean daily market return, Market
Volatility is the standard deviation of market returns (both measured within three weeks prior to
the offer date), and #IPO is the number of other IPOs within 12 months prior to the offer date.
Secondary Market equals one if an IPO firm is listing on a secondary market and zero otherwise.
The descriptive statistics reported in Table 3 are consistent with prior IPO studies (e.g. Loughran
et al. 1994).
Regression Analysis
                                                            
19

When counting the number of potentially comparable firms for an IPO firm, we include only those listed industry
peers for which sales data (from Datastream) are available for the fiscal period ending in the three months prior to
the IPO offer date.

18
 
 

 

Table 4 reports the results of estimating Equations (1a) and (1b). Note, because our
mandatory adoption test sample consists of matched pairs of IPOs, matched by country and
industry, and we include fixed effects for each pair of matched IPOs, we effectively control for
country- and industry-level fixed effects. In Equation (1a) the variable of interest is
IFRS×log(1+Comp). H1 predicts that IFRS will generate enhanced overall comparability
compared to domestic GAAP, resulting in reduced IPO underpricing, i.e., β3 < 0.
As can be seen in Table 4, β2 is significantly negative (p<0.05, two-tailed) showing that,
in general, a greater number of comparable firms is associated with a significant decrease in IPO
underpricing. However, β3 is not statistically different from zero, so we reject H1 and find no
evidence of a difference in overall comparability between domestic GAAP and IFRS. As can be
seen in Panel B, the coefficient estimate of total comparability for IFRS firms, (β2 + β3), is
negative, but is not significant at conventional levels. However, this seems to be due to greater
noise in the Comp variable for IFRS firms (see discussion below).
< Insert Table 4 about Here >
H2 predicts that only IFRS-reporting peers in high enforcement jurisdictions provide
genuine comparability for IFRS-reporting IPOs. Equation (1b) tests H2. The main variable of
interest is IFRS×log(1+CompStrong /(1+CompWeak)). CompStrong is the raw number of comparable
firms domiciled in strong enforcement countries, so H2 predicts that β7 < 0. As can be seen in
Table 4, consistent with this prediction, β7 is significantly negative (p<0.01, one-tailed).
Panel B of Table 4 shows the results of additional statistical tests that are relevant to H2.
For IFRS-reporting IPOs, the impact on IPO underpricing of listed industry peers domiciled in
weak enforcement countries is measured by the coefficients on log(1+CompWeak) and
IFRS×log(1+CompWeak), i.e., (β4 + β6). As can be seen in Panel B, (β4 + β6) is positive but not
19
 
 

 

statistically significant, indicating that IFRS-reporting IPOs do not benefit from having listed
industry peers located in weak enforcement countries. On the other hand, for IFRS-reporting
IPOs, the impact on IPO underpricing of listed industry peers domiciled in strong enforcement
countries

is

measured

by

the

coefficients

on

log(1+CompStrong/(1+CompWeak))

and

IFRS×log(1+CompStrong/(1+CompWeak)), i.e., (β5 + β7). Panel B shows that (β5 + β7) is significantly
less than zero (p<0.01, one-tailed). In summary, consistent with H2, the results show that IFRSreporting IPOs benefit only from having listed industry peers located in strong enforcement
countries: only these peers seem to provide genuine comparability.20
For a domestic GAAP-reporting IPO, the industry peers are domiciled in the same
country. If a domestic GAAP-reporting IPO is from a weak enforcement country, then β4
approximates the impact (on IPO underpricing) of the overall level of comparability derived
from listed industry peers in the same country. For IFRS-reporting IPOs (β4 + β6) approximates
the impact (on IPO underpricing) of the overall level of comparability derived from listed
industry peers in all countries. While (β4 + β6) is not statistically significant, we find that β6 is
significantly positive (p<0.05, two-tailed). The significantly positive β6 indicates that listed peers
based in weak enforcement jurisdictions provide less comparability under IFRS than under
domestic GAAP.21
The lack of statistical significance we found for H1 seems to be due to greater noise in
the Comp variable for IFRS firms: when we re-estimate Equation (1a) replacing Comp with
                                                            
20

 Our results speak to the average level of overall comparability. Cascino and Gassen (2015) study compliance
incentives at the country, region, and firm levels. They find evidence that firm-level reporting incentives play a role
in determining the level of comparability. Thus, within IFRS, it is possible that some IFRS-reporting firms in weak
enforcement jurisdictions but with high firm-level reporting incentives will provide meaningful comparability.
21
Taken at face value this result suggests that, when coupled with a weak enforcement environment, the principlesbased IFRS actually provide less comparability than domestic GAAP, i.e., in weak enforcement jurisdictions per
unit comparability from domestic listed peers actually decreases following mandatory IFRS adoption. However, in
our mandatory adoption test sample only 10 IPO firms (from Greece and the Philippines) are domiciled in weak
enforcement countries (see Panel A of Table 2). As a result, we caution readers as to the generalizability of this
result.

20
 
 

 

CompStrong we find that (β2 + β3) is now significantly negative (p=0.02, one-tailed). Since
CompStrong is the total number of listed peers based in strong enforcement jurisdictions, it
provides for a more homogenous set of comparable firms than Comp. Also, this suggests that
IFRS do provide enhanced overall comparability compared to domestic GAAP, but only if one
restricts the set of comparable firms to those listed industry peers domiciled in high enforcement
jurisdictions.
< Insert Table 5 about Here >
Table 5 shows the results of our DID tests. These tests parallel our estimates of Equations
(1a) and (1b) reported in Table 4, which use just the mandatory adoption test sample. To estimate
our DID models, we pool the mandatory adoption test sample of 493 matched pairs of IPOs from
mandatory IFRS adopting countries with a control sample of 986 matched pairs of IPOs from
non-IFRS adopting countries. All the IPO firms in our control sample report in domestic GAAP.
Panel A of Table 5 reports the results for our DID estimates of Equation (1a) and show that,
contrary to the prediction of H1, β3 is not significantly different across our test and control
samples. Panel B of Table 5 reports the results for our DID estimate of Equation (1b). Consistent
with our prediction for H2, and our earlier results reported in Table 4, we find that β7 is
significantly more negative for the test sample than for the control sample (p<0.05, one-tailed).
As discussed earlier, interpreting the difference in the β1 coefficient between the test and
control samples is problematic. This is because the difference in β1 between the test and control
samples reflects not only any difference from any changes in reporting quality arising from
mandatory IFRS adoption, but also any differences in macroeconomic shocks between our test
and control sample firms (which, by necessity, are drawn from different countries).

21
 
 

 

The results for our analysis of the test sample alone (Table 4) and our DID analysis of the
pooled test and control samples (Table 5) show a consistent result: IFRS-reporting IPOs do (do
not) benefit from having more listed industry peers located in strong (weak) enforcement
jurisdictions. These results suggest that enforcement quality is critical in generating enhanced
comparability following mandatory IFRS adoption. To evaluate the economic significance of our
results, we substitute the mean values of the variables shown in Table 3 into the estimated
equations shown in Table 4. We find that, relative to a firm with no comparable firm, the
reduction in IPO underpricing from the average number of listed peers is 3.3% (7.9%) for
domestic GAAP- (IFRS-) reporting IPOs, indicating that, on average, IFRS provides incremental
comparability that reduces underpricing by 4.6%. For an average IPO in our sample, this
translated into a saving of over $2 million.
V. VOLUNTARY IFRS ADOPTER SAMPLE
Our first set of analysis suggests that enforcement quality is critical in determining the
extent to which IPO firms benefited from enhanced comparability following mandatory IFRS
adoption. A number of prior studies suggest that the effects of mandatory IFRS adoption depend
on firms’ reporting incentives that are shaped by the quality of countries’ enforcement
environments (Daske et al. 2008; Li 2010; Byard et al. 2011). Prior studies also suggest that
firms’ reporting incentives are critical in mediating the effects of IFRS adoption, in particular, in
the context of voluntary IFRS adoption (Leuz and Verrecchia 2000; Ashbaugh and Pincus 2001).
A number of countries (e.g., Germany) allowed voluntary IFRS adoption prior to 2005
Using a sample of IPOs from these countries, in this section we test if IPO firms that voluntarily
adopted IFRS also benefited from enhanced overall comparability (relative to IPO firms that
chose to report in domestic GAAP). The overall level of comparability from listed industry peers
22
 
 

 

could be different for IFRS IPOs vs. domestic GAAP IPOs because: (1) the total number of
comparable firms is different, and (2) the level of comparability per listed industry peer is
different. In contrast to mandatory IFRS adoption, it is unlikely that IFRS provides for a “far
greater” number of listed industry peers for voluntary IFRS adopters than would domestic GAAP.
However, in the pre-2005 voluntary adoption setting, it is important to recognize that any listed
industry peers that report in IFRS are themselves voluntary IFRS adopters. As such, these peers
are likely to have strong firm-level incentives for transparency (Leuz and Verrecchia 2000), so
they can be expected to rigorously implement the reporting requirements of IFRS. We expect
these (voluntary adopter) peer firms to provide a higher level of comparability per listed industry
peer.
In summary, in the pre-2005 period, we expect that IPO firms that voluntarily report in
IFRS will benefit from enhanced comparability relative to IPO firms that chose to report in
domestic GAAP. We expect this because, in IFRS, the industry peers are themselves voluntary
IFRS adopters with strong firm-level reporting incentives. It follows that there is no need to split
the listed industry peers into CompStong and CompWeak; essentially we assume that, in the
voluntary IFRS adoption setting, for IFRS-reporting IPOs, all of listed industry peers are
CompStrong type firms.22
For our voluntary IFRS adoption sample, we select a sample of IPO firms that went
public in 2003 and 2004 in countries where (1) IFRS were mandated in 2005, and (2) there is at
                                                            
22

Rigorous implementation of IFRS can come from a strong country-level enforcement environment, or strong firmlevel reporting incentives (see Byard et al. 2011; Cascino and Gassen 2015). In a strong enforcement environment,
all firms are expected to rigorously implement the ascribed standards; but, in a weak enforcement environment there
is more scope for firm-level reporting incentives to affect variation in reporting quality and, hence, comparability. In
IFRS, because all of the comparable firms have also voluntarily adopted IFRS, these comparable firms are all likely
to have strong firm-level reporting incentives. There is therefore less scope for the quality of country-level
enforcement environments to affect the quality of the implementation of IFRS among these comparable firms. So for
our voluntary adoption sample, we do not separate comparable firms into those domiciled in strong enforcement
countries (CompStrong) and those domiciled in weak enforcement countries (CompWeak).

23

 
 

 

least one IFRS-reporting and one domestic GAAP-reporting IPO in the country in 2003-2004.
Additionally, we include Chinese and Singaporean IPOs as the stock exchanges in these
countries permitted reporting in different accounting standards over this period (see Panel B of
Table 1). Our sample consists of 591 IPOs, of which 557 (34) report in domestic GAAP (IFRS);
the relatively small proportion of voluntary IFRS adopters is consistent with prior studies
(Cuijpers and Buijink 2005; Christensen 2008). Panel B of Table 2 shows the country
distribution of the sample: for example, there are 21 IPOs in France, of which 20 (1) report in
domestic GAAP (IFRS).23 The descriptive statistics for the 557 (34) IPOs reporting in domestic
GAAP (IFRS) are shown in Panel A (B) of Table 6, and are comparable to those of prior IPO
studies (e.g., Loughran et al. 1994).
< Insert Table 6 about Here >
An obvious empirical challenge to identifying the effect of voluntary IFRS adoption on
IPO underpricing is the fact that these firms self-select to use IFRS. Therefore, in our empirical
estimation, we need to control for self-selection. If IFRS provide for a higher level of disclosure
than domestic GAAP, then IPO firms that choose to report in IFRS are likely to have stronger
firm-level reporting incentives than those firms that choose to report in domestic GAAP. Such
(unobservable) firm-level reporting incentives are likely to be correlated with the degree of IPO
underpricing. It is critical in such a setting to empirically distinguish between the effects of the
differences in firm characteristics that cause a firm to choose to use IFRS (vs. domestic GAAP)
and the effect of IFRS per se (see Leuz and Verrecchia 2000).
                                                            
23

Note, while the UK, Sweden, France, and Italy did not permit domestic listed firms to use IFRS prior to 2005, it is
still possible for a firm to voluntarily report in IFRS in these countries in the pre-2005 period. This can happen if:
(1) a firm chooses to issue two sets of financial statements, one in (the required) domestic GAAP and one
(voluntarily) in IFRS; or (2) within domestic GAAP a firm chooses accounting policies that are IFRS-compliant, so
that its financial statements are compliant with both domestic GAAP and IFRS. We include IPOs from these
countries in our voluntary adoption sample, but our results are robust to dropping these IPOs from the sample.

24
 
 

 

For this analysis, rather than matching each IFRS-IPO with a matched domestic GAAP
IPO one-to-one, we use all available IPO observations (from countries that allowed voluntary
IFRS adoption before 2005) and adopt an endogenous treatment model that controls for selfselection via an Inverse Mills Ratio. An endogenous treatment effect model (Heckman 1979;
Greene 2003) mitigates self-selection bias by controlling for the potentially unobservable
managerial decision variables in a two-stage regression model. At the first-stage, we construct a
probit model for firms’ decision to adopt IFRS or domestic GAAP (see Equation (2a)). This firststage probit model provides an estimate of the Inverse Mills Ratio, which we include as a control
for self-selection in a second-stage OLS estimate (Equation (2b)):
Prob(IFRS) = Z’γ + ε ;

(2a)

IniRet = θ0 + θ1 IFRS + θ2 log(1+Comp) + θ3 IFRS× log(1+Comp)
+ δ Inverse Mills Ratio + Controls + υ.

(2b)

where Z is a vector of the determinants of an IPO firm’s choice between IFRS and domestic
GAAP. Similar to Leuz and Verrecchia (2000), we include cross-listing, return on assets (ROA),
and leverage as determinants of firms' choice of accounting standards; given our IPO setting, we
use log(1+Proceeds) as a measure of size. Additionally, because of the international setting, we
include IFRSdiff, the difference between domestic GAAP and IFRS (Bae, Tan and Welker 2008),
and log(1+CompDomestic), the number of industry peers reporting in domestic GAAP, as possible
determinants of firms' choice of accounting standards. A larger difference between domestic
GAAP and IFRS, or fewer comparable firms reporting in domestic GAAP, may prompt an IPO
firm to choose to report in IFRS. The eight variables we use as determinants of firms' choice of
accounting standards are explained in the endnotes of Table 6.
In Equation (2b), Controls includes not only control variables for IPO firm characteristics
(as in Equation (1b)), but also controls for country-level institutions that may affect IPO
25
 
 

 

underpricing.24 Specifically, we include a dummy variable, Common, for common law vs. code
law countries. IPO underpricing may vary across countries due to differences in the level of
capital market development, legal system, the IPO process, investor protection etc., all of which
are likely to differ across common and code law countries.25 We also include three of the eight
controls from the first stage model, since they are likely to influence IPO underpricing (Lennox,
Francis, and Wang 2011). Controls are defined in the endnotes of Tables 3 and 6. Finally,
Equation (2b) also includes the Inverse Mills Ratio calculated from Equation (2a).
IFRS is a dummy variable coded one (zero) for an IPO firm that chooses to report in
IFRS (domestic GAAP). Thus, controlling for self-selection bias, the effect of voluntary IFRS
adoption on IPO underpricing is identified by θ1 (Wooldridge 2010). This variable picks up the
effect of any change in reporting quality associated with voluntary IFRS adoption on IPO
underpricing. For domestic GAAP-reporting IPOs, θ2 approximates how a 1% increase in the
number of listed peers will affect IPO underpricing; θ3 approximates how the effect of a 1%
increase in the number of listed peers on IPO underpricing differs between IFRS and domestic
GAAP. Thus, for a voluntary IFRS adopter (θ2+θ3) approximates how a 1% increase in the
number of IFRS-reporting listed peers will affect IPO underpricing. Since we expect that there
will be a higher level of overall comparability under IFRS than under domestic GAAP, we
expect that θ3 < 0.
< Insert Table 7 about Here >

                                                            
24

Recall that for our analysis of mandatory IFRS adoption, we use a matched-pairs sample where observations are
matched by industry, country, and proceeds. As a result, we do not include country-level institutional characteristics
as control variables in Equations (1a) and (1b). However, since we do not employ a matched-pair sample here, we
need to include such country-level control variables in our estimates of Equation (2b).
25
On average, common law countries tend to have more developed capital markets and better levels of investor
protection. As an alternative, we also use the investor protection index of Djankov et al. (2008) with consistent
results.

26
 
 

 

The results are presented in Table 7. The results for Equation (2a), the first stage probit
model, show that IPO firms that are cross-listed, have fewer comparable firms reporting in
domestic GAAP, or are listing in countries with larger difference between domestic GAAP and
IFRS are all significantly more likely to choose to report in IFRS than in domestic GAAP
(p<0.01, two-tailed, for all). The results for Equation (2b) show a significant and negative
coefficient (p<0.05, one–tailed) on IFRS×log(1+Comp), indicating that voluntary IFRS adopting
IPOs benefit from enhanced overall comparability compared to domestic GAAP-reporting IPOs.
IPO firms in common law countries and those listed on secondary markets have significantly
lower IPO underpricing (p<0.01, two-tailed). Also, Panel B shows that (θ2+θ3) is significantly
negative (p<0.06, one-tailed). Finally, the estimate on Inverse Mills Ratio in Equation (2b) is not
statistically significant, possibly because the first stage model captures firms' choice of
accounting standards. So there does not appear to be an omitted unobservable variable that drives
both firms’ accounting standards choice and IPO underpricing. This indicates that sample
selection does not result in a significant bias in this OLS model.
In summary, there are two noteworthy results on comparability. First, the results for
Equation (2a) show that when an IPO firm has fewer listed industry peers reporting in domestic
GAAP, the firm is more likely to choose to report in IFRS. Second, the results for Equation (2b)
show that, relative to domestic GAAP-reporting industry peers, IFRS listed industry peers are
significantly negatively associated with a reduction IPO underpricing―indicating that IFRS
provide enhanced overall comparability. We argue that voluntary IFRS adoption is likely to
provide enhanced overall comparability not because IFRS provide for a far greater number of
comparable firms (as in the case of mandatory IFRS adoption), but because comparability per
listed industry peer is likely to be higher for IFRS than for domestic GAAP (because, by
27
 
 

 

definition, the comparable firms are themselves voluntary adopters with strong reporting
incentives). Consistent with this expectation, while IFRS provide for enhanced overall
comparability, the number of comparable firms is not much greater in IFRS than in domestic
GAAP: mean Comp is 31.6 (25) for IFRS (domestic GAAP)―see Table 6. Taken together, the
results suggest that in a voluntary IFRS adoption setting, IFRS-reporting IPOs benefit from the
stronger reporting incentives of their listed industry peers.
VI. ADDITIONAL ANALYSI AND ROBUSTNESS
We verify that our inferences are robust to a number of additional analysis and robustness
tests. First, we find that our results are robust to the adoption of the EU’s Prospectus Directive
(PD), a key regulatory change that is likely to have affected the IPO market in Europe. 26
Christensen et al. (2013, 2014) show that, when studying the effects of mandatory IFRS adoption,
it is important to control for concurrent regulatory changes in Europe. Second, we verify that our
main inferences are robust to excluding Australian firms from our mandatory adoption test
sample. Third, a number of prior studies suggest that the effects of mandatory IFRS adoption are
stronger in countries with large differences between domestic GAAP and IFRS. In untabulated
analysis, using the GAAP differences index of Bae et al.’s (2008), we find no evidence that our
results are due only to IPO firms domiciled in countries with high values of GAAP difference.
Finally, we also test whether listed US GAAP-reporting firms provide additional comparability
(in addition to Comp or Compstrong) for IFRS-reporting IPOs than for domestic GAAP-reporting
IPOs. Given the high quality of US GAAP and the convergence between US GAAP and IFRS,
US GAAP-reporting industry peers may provide incremental comparability for IFRS-reporting
                                                            
26

During our sample period the EU adopted the Prospectus Directive (2003/71/EC), requiring all IPO firms going
public in EU member countries to provide prescribed disclosures in a standardized prospectus. As a regulatory
change directly affecting the public disclosure requirements of IPO firms, the Prospectus Directive could affect IPO
underpricing.

28
 
 

 

firms (Barth, Landsman, Lang, and Williams 2012). However, we find no evidence that listed
US GAAP-reporting firms provide additional comparability for IFRS-reporting IPOs over and
above that provided by listed IFRS-reporting industry peers. This may be due to the fact that, on
average, IFRS already provide for a large number of listed peers, so that the scope for US
GAAP-reporting listed industry peers to provide additional comparability is quite limited.
VII. CONCLUSION
This study examines the effect of mandatory and voluntary IFRS adoption on IPO
underpricing; we focus on the impact of enhanced comparability under IFRS compared to
domestic GAAP. First, while we find that mandatory IFRS adoption provides a far greater
number of potentially comparable firms throughout the world, our results suggest that not all
IFRS-reporting industry peers provide genuine comparability for IPO firms: the benefits of
enhanced overall comparability under IFRS derive only from those listed industry peers
domiciled in high-quality enforcement environments. Enforcement quality is thus a key
determinant of the positive externality of enhanced comparability under IFRS. Second, we
provide new evidence indicating that voluntary IFRS adopters also benefit from enhanced
comparability. For the voluntary adoption setting, we find that (1) IPO firms are more likely to
choose to report in IFRS when domestic GAAP provides for fewer comparable firms; and (2) for
IFRS-reporting IPOs, the enhanced comparability reduces IPO underpricing relative to that of
domestic GAAP IPO firms.
In a recent study, Hong et al. (2014) show that changes in reporting quality following
mandatory IFRS adoption help explain change in IPO underpricing. Our results complement
their finding by showing that changes in comparability following mandatory IFRS adoption also
help explain changes in IPO underpricing. This study also makes a number of distinct
29
 
 

 

contributions. First, we contribute to the literature on the benefits of both voluntary and
mandatory IFRS adoption. In particular, we add to recent research on the effect of mandatory
IFRS adoption on comparability (Brochet et al. 2013; DeFond et al. 2011; Lang et al. 2010; Yip
and Young 2012; Wang 2014). Second, we provide new evidence regarding the importance of
enforcement quality (or reporting incentives) in generating enhanced comparability under IFRS.
Prior studies emphasize the important role of reporting incentives and enforcement quality in
determining firms' reporting outcomes (Ball et al. 2000, 2003; Ball 2006; Burgstahler, Hail and
Leuz 2006; Daske et al. 2008; Li 2010; Byard et al. 2011; Hong et al. 2014). We add to this
stream of literature by highlighting an important positive externality of enforcement quality:
enhanced comparability. This result also serves to provide new evidence regarding the
information externalities associated with high quality enforcement (Dye 1990; Bushee and Leuz
2005). Third, for voluntary IFRS adoption our results add new evidence that comparability is
both a factor in firms’ choice to voluntarily adopt IFRS (see Ashbaugh 2001; Cuijpers and
Buijink 2005), and a benefit that firms derive from voluntary IFRS adoption (Leuz and
Verrecchia 2000; Ashbaugh and Pincus 2001; Covrig et al. 2007). Finally, our results contribute
to the IPO literature―specifically, by advancing our understanding of the role of financial
disclosures in mitigating IPO underpricing (Leone et al. 2007; Boulton et al. 2011).
Our study has a number of caveats. While we identify the impact of mandatory IFRS
adoption using a DID design, by necessity our test and control samples are from different
countries. While we attempt to incorporate much of the institutional complexity of the setting,
we can’t rule out the possibility that there were other important institutional changes over our
sample period. Finally, our voluntary adopter sample uses just 34 firms that choose to report in
IFRS.
30
 
 

 

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35
 
 

 

TABLE 1
Sample Selection Procedures
Panel A: Mandatory IFRS Adopter Sample
Description
IPO firms issuing ordinary common shares around the world during 2006-2007
(First trading-day return data are unavailable)
(Accounting standards data are unavailable)
(Data for other control variables are unavailable)
(Listing in countries that do not mandate IFRS in 2005)
(Listing on European exchanges that allow domestic GAAP after 2005)
(Not matched with domestic industry-peer IPOs before 2005)
IFRS-reporting IPOs in 2006 and 2007 from Countries that Mandated the Adoption of
IFRS in 2005 with available Benchmark Domestic GAAP Reporting IPO firms
Matched (Benchmark) Domestic GAAP-reporting IPOs in 2003 and 2004 in the Same
Industries and the Same Countries
Mandatory Adoption Test Sample: 493 IFRS reporting IPOs from 2006-2007, with 493
domestic GAAP-reporting IPOs from 2003-2004, matched by country and industry
Control Sample: 628 IPOs from the period 2003-2004 with 628 matched IPOs from the
period 2006-2007, matched by country and industry. These IPOs are from countries that
did not mandate IFRS over our sample period, so all 1,256 IPOs report in domestic GAAP
Panel B: Voluntary IFRS Adoption Sample
IPO firms issuing ordinary common shares around the world in 2003-2004
(First trading-day return data are unavailable)
(Accounting standards data are unavailable)
(Other control variables are unavailable)
(Listings in countries that did not mandate IFRS in 2005)
Listings in countries that allowed multiple accounting standards over this period
(Listings in countries that have no IPO firms that report in IFRS)
Voluntary Adoption Sample

# of observations
3,380
(903)
(128)
(40)
(1,154)
(406)
749
(256)
493
493
986

1,256

2,316
(376)
(132)
(148)
(1,089)
244
(224)
591

IPO data for the sample period 2003-2004 and 2006-2007 are from the SDC database. Only IPOs that SDC classifies
as “Common Shares,” “Ord/Common Shs,” “Ordinary Shares,” or “Class A Ord Shs” are included in the samples. If
there are multiple observations for an IPO on the same day, only one observation is retained. The closing market
prices on the first trading-day are from SDC; accounting standards data are from Datatream, or Compustat Global
when Datastream data is unavailable.
Panel A describes the selection of our mandatory adoption test sample (and the associated control sample). We first
select only IPO firms subject to mandatory IFRS adoption, i.e., 2006-2007 IPOs from countries that mandated the
adoption of IFRS in 2005. IPO firms listing on secondary exchanges that allow both IFRS and domestic GAAP after
2005 (e.g., AIM in UK) are excluded from the sample (406 IPOs). We require that each IFRS-reporting IPO be
matched with a domestic GAAP-reporting IPO from the same country, the same industry, and closest proceeds
(from the pre-2005 period). This results in a final mandatory adoption test sample of 493 matched pairs IPOs: 493
treatment IPOs that went public in a mandatory IFRS reporting regime (2006 and 2007), and 493 matched
benchmark IPOs that went public in the same countries and industries, but in a mandatory domestic GAAP-reporting
regime (from 2003 and 2004).
Using a similar sample selection procedure, we also form a control sample of IPO firms that listed in countries that
did not mandate IFRS adoption during our sample period (i.e., up to the end of 2007). The control sample is also
comprised of matched pairs of IPOs, matched by country, industry and closest proceeds, where one IPO is from the
period 2003 to 2004 and the other IPO is from the period 2006 to 2007. For consistency, only IPO firms in the same

36
 
 

 

industries as our mandatory adoption test sample firms are included in the control sample. The control sample
consists of 628 pairs of matched IPOs (1,256 IPO firms in total): 628 IPOs from the period 2003 and 2004, and
another 628 (matched) IPOs from the period 2006 and 2007. All IPOs in the control sample report in domestic
GAAP.
Panel B describes the selection of our voluntary adoption sample. For the sample period 2003 and 2004, we identify
a sample of IPOs from countries where firms had a choice of using domestic GAAP or IFRS. After excluding
observations with no first trading-day return (376), no accounting standards data (132), and with missing data for
other control variables (148), we have 1,660 observations with available data. We retain IPOs from countries that
mandatorily adopted IFRS in 2005 and where there is at least one IFRS-reporting and one domestic GAAP-reporting
IPO in the period 2003-2004. This includes both (1) countries that specifically permitted voluntary IFRS adoption
prior to 2005 (e.g., Germany); and (2) countries that required domestic GAAP reporting for domestic listed firms
prior to 2005 (i.e., France, UK and Sweden), but where at least one domestic IPO firm listed using IFRS (these are
cases where firms choose to provide two sets of financial reports, in domestic GAAP and IFRS, or where a firm
makes accounting policy choices within domestic GAAP such that it can also be compliant with IFRS). We further
eliminate observations listed in countries that did not mandate IFRS in 2005 (1,089), and add firms listed in
countries that allowed multiple accounting standards (i.e., China and Singapore, 244 observations) over our sample
period. These procedures result in a final voluntary adoption sample of 591 IPOs, 34 (557) of which are IFRSreporting (domestic GAAP-reporting). The relatively small number voluntary IFRS adopters is consistent with prior
studies (Cuijpers and Buijink 2005; Christensen 2008).

37
 
 

 

TABLE 2
Composition of Samples by Country
Panel A: Mandatory IFRS Adoption Test and Control Samples
IniRet

Australia
France
Greece
Hong Kong
New Zealand
Norway
Philippines
Sweden
United Kingdom
Brazil
India
Indonesia
Japan
Malaysia
South Korea
Taiwan
Thailand
United States
Total

Test/Control
Sample
Test
Test
Test
Test
Test
Test
Test
Test
Test
Control
Control
Control
Control
Control
Control
Control
Control
Control

# of
observations
672
32
2
44
6
24
8
2
196
2
2
4
392
74
162
122
22
476
2,242

Panel B: Voluntary IFRS Adoption Sample
# Domestic
#IFRS
GAAP IPOs
IPOs
China
150
2
France
20
1
Germany
1
3
Greece
6
2
Hong Kong
65
2
Italy
1
4
Poland
3
2
Singapore
79
9
Sweden
2
1
UK
230
8
Total
557
34

Domestic GAAPreporting IPO firms
21.1%
6.8%
42.5%
10.9%
5.9%
10.5%
1.9%
-24.8%
23.6%
0.5%
24.0%
12.9%
52.4%
42.0%
34.0%
3.4%
26.6%
11.7%

IFRS-reporting
IPO firms
27.3%
3.4%
23.5%
33.0%
9.2%
5.0%
9.2%
13.7%
17.3%
-6.7%
88.4%
56.8%
35.3%
17.9%
42.8%
55.2%
16.1%
10.8%

Domestic GAAPreporting IPO firms
14.6%
4.3%
3.6%
6.9%
5.3%
0.8%
12.8%
10.0%
0.8%
9.0%
10.0%

IFRS-reporting
IPO firms
15.4%
0.8%
5.8%
0.8%
11.4%
5.8%
14.9%
10.6%
7.2%
11.6%
9.5%

IniRet is the degree of IPO underpricing, measured as the first trading-day returns.
Panel A shows the country distribution of the mandatory adoption test sample and the associated control sample.
The mandatory adoption test sample is distributed across the following industries: 511 firms in mining and
construction, 113 in manufacturing, 28 in transportation and communication, 16 in wholesale and retail trade, 152 in
finance, 156 in services, 6 in agriculture, and 4 in other industries. The mandatory adoption test sample is distributed
across years as follows: 186 in 2003, 307 in 2004, 169 in 2006, and 324 in 2007.
Panel B shows the country distribution of the voluntary adoption sample. The first (second) column shows the
distribution of the domestic GAAP-reporting (IFRS-reporting) IPOs by country. The industry distribution of the

38
 
 

 

sample is as follows: 7 firms in agriculture, 62 in mining and construction, 264 in manufacturing, 52 in
transportation and communication, 31 in wholesale and retail trade, 63 in finance, 109 in services, and 3 in other
industries. The voluntary adoption sample is distributed across years as follows: 191 in 2003 and 400 in 2004.

39
 
 

 

TABLE 3
Descriptive Statistics: Mandatory IFRS Adoption Test Sample
Panel A: IFRS-Reporting IPOs (N=493)
Min.
-26.7%
2
0
0
1.2
-3.8%
0
-31.3%
36.1%
0
0

Q1
1.1%
52
25
17
2.7
0
0
-1.9%
64.0%
8
0

Median
12.1%
142
116
29
5.6
0
0
9.0%
78.3%
12
0

Q3
31.8%
263
225
45
31.1
0
0
21.5%
104.8%
17
0

Max.
207.3%
564
522
112
56.1
5.4%
1
56.4%
188.6%
30
1

Panel B: Domestic GAAP-Reporting IPOs (N=493)
IniRet
20.1%
-26.7%
Comp
32.3
0
32.0
0
CompStrong
0.2
0
CompWeak
Proceeds
36.5
1.2
Partial Adjustment
0.0%
-3.8%
Cross Listing
1.0%
0
Market Return
11.7%
-31.3%
Market Volatility
57.3%
26.5%
#IPO
8.5
0
Secondary Market
1.6%
0

-2.0%
1
1
0
2.6
0
0
3.4%
37.3%
4
0

5.0%
6
6
0
5.3
0
0
12.6%
47.1%
8
0

22.8%
62
62
0
31.9
0
0
20.7%
65.0%
11
0

207.3%
159
159
32
656.1
5.4%
1
56.4%
188.6%
30
1

IniRet
Comp
CompStrong
CompWeak
Proceeds
Partial Adjustment
Cross Listing
Market Return
Market Volatility
#IPO
Secondary Market

Mean
23.9%
182.8
146.8
36.6
54.0
0.2%
13.2%
9.0%
85.6%
12.5
15.4%

Table 3 presents descriptive statistics for the mandatory adoption test sample of 986 IPO firms from mandatory
IFRS adopting countries that are used for the analyses in Tables 4 and 5. Of these 986 observations, 493 report in
IFRS (IFRS = 1. i.e., IPOs that went public in 2006 and 2007) and 493 report in domestic GAAP (IFRS=0, i.e., IPOs
that went public in 2003 and 2004). Panel A shows the descriptive statistics for the 493 treatment IFRS-reporting
IPOs; Panel B shows the descriptive statistics for the 493 benchmark (matched) domestic GAAP-reporting IPOs.
The domestic GAAP-reporting IPOs are matched with the IFRS-reporting IPOs by industry, country, and the closest
proceeds.
Variable Definitions:
IniRet = (the ratio of closing and offer prices of the first trading-day) – 1;
IFRS = One for an IFRS-reporting IPO, i.e., an IPO from the period 2006 and 2007; zero for a
domestic GAAP-reporting IPO, i.e., an IPO from the period 2003 and 2004;
Comp = The raw number of listed industry peers that use the same set of accounting standards as
an IPO firm. For a domestic GAAP-reporting firm, Comp is equal to the raw number of
domestic listed industry peers. For an IFRS-reporting firm, Comp is equal to the raw
number of listed industry peers around the world;
CompStong = The raw number of listed industry peers that are domiciled in strong enforcement
countries. A country is classified as having a strong (weak) enforcement environment if
the country’s “Rule of Law” index (from Kaufmann et al. 2007) is greater than (less than)

40
 
 

CompWeak
Proceeds
Partial Adjustment
Cross Listing
Market Return
Market Volatility
#IPO
Secondary Market

the median value (0.74) of the countries that account for over 99.5% of the world
capitalization;
= The raw number of listed industry peers that are domiciled in weak enforcement
countries;
= Proceeds size expressed in millions US dollars, scaled by the US CPI;
= The difference between the offer price and the median value of the initial price range
(Hanley 1993). If the initial price range is missing in SDC, we set the partial adjustment
to zero;
= One if an IPO firm is cross-listed; zero otherwise;
= The average daily market return over the three weeks prior to the offer date in the country
where an IPO firm is listed;
= The standard deviation of the daily market returns over the three weeks prior to the offer
date in the country where an IPO firm is listed;
= The number of IPO firms that go public in the same country during the 12 months prior
to the offer date;
= One if an IPO firm is listed on a secondary stock (also known as an “exchange regulated”
market) exchange (e.g., IPOs listing on AIM in 2007); zero if an IPO is listed on a
primary market (also known as an “EU regulated” market).

41
 
 

TABLE 4
Comparability and IPO Underpricing: Mandatory IFRS Adoption
IniRet = X’β + β1 IFRS + β2 log(1+Comp) + β3 IFRS×log(1+Comp)
+ Controls + υ,

(1a)

IniRet = X’β + β1 IFRS + β4 log(1+CompWeak) + β5 log(1+CompStrong / (1+CompWeak))
+ β6 IFRS×log(1+CompWeak) + β7 IFRS×log(1+CompStrong / (1+CompWeak))
+ Controls + υ
.

(1b)

Panel A: Regression Results
Equation (1a)
IFRS
log(1+Comp)
IFRS×log(1+Comp)
log(1+CompWeak)
log(1+ CompStrong / (1+CompWeak))
IFRS×log(1+CompWeak)
IFRS×log(1+CompStrong /(1+CompWeak))

β1
β2 
β3 
β4 
β5 
β6 

Equation (1b)

Predict

Coeff.

z-stat.

(-)

0.236
-0.025**
-0.009

(1.53)
(-2.01)
(-0.25)

β7 

Predict

(-)

Coeff.

z-stat.

0.071

(0.49)

-0.023
-0.020*

(-0.63)
(-1.81)

0.078**

(2.14)

-0.094***

(-5.06)

-0.086
-0.096
0.194
0.175
0.003
-0.120
-0.390*

(-1.34)
(-0.05)
(0.79)
(1.02)
(0.03)
(-1.62)
(-1.92)

 

Control Variables:
log(1+Proceeds)
Partial Adjustment
Cross Listing
Market Return
Market Volatility
log(1+#IPO)
Secondary Market
R2
Adjusted Clustered standard errors
# of fixed effects for matched pairs
# of observations

β8 
β9 
β10 
β11 
β12 
β13 
β14 

-0.075
-0.016
0.211
0.171
-0.021
-0.107
-0.350

(-1.18)
(-0.01)
(0.87)
(1.16)
(-0.17)
(-1.46)
(-1.61)

50.8%
Yes
493
986

51.8%
Yes
493
986

 
Panel B: Linear Combination Tests
Predict
β2+ β3
β4+ β6
β5+ β7

(-)

Equation (1a)
Coeff.
t-stat.
-0.035
(-1.24)

Equation (1b)
Coeff.
t-stat.
0.055
-0.114***

 
(-)

(1.29)
(-9.38)

This table presents the estimates of Equations (1a) and (1b). IniRet, the dependent variable, is the degree of IPO
underpricing measured by the first trading-day return. IFRS equals one (zero) if an IPO firm reports in IFRS
(domestic GAAP). Comp equals the raw number of industry peers that use the same set of accounting standards as
an IPO firm. CompStrong (CompWeak) is Comp counted across industry peers that are domiciled in strong (weak)
enforcement countries, i.e., where the 2005 value of the “Rule of Law” index (Kaufmann et al. 2007) is greater (less)
than the median value across all countries (0.74). See the endnotes of Table 3 for definitions of the control variables. 
Standard errors are clustered by country and month. We report significance levels based upon one- (two-) tailed pvalues for variables where we have (do not have) a directional prediction; 10%, 5%, and 1% are indicated by *, **,
and ***, respectively.

42
 
 

TABLE 5
Comparability and IPO Underpricing: Summary of DID Results for Mandatory IFRS Adoption
Panel A: Re-Estimation of Equation (1a) using Difference-in-Difference Specification
Test Sample
Prediction
Coeff.
t-stat.
β1
0.236
(1.53)
IFRS
β2
-0.025** (-2.01)
log(1+Comp)
β3
IFRS×log(1+Comp)1
(-)
-0.009
(-0.25)
2
R
50.8%
Adjusted standard errors
Yes
# of fixed effects for matched pairs
493
# of observations
986

Control Sample
Coeff.
t-stat.
0.145
(1.04)
-0.051*
(-1.81)
-0.030
(-0.97)
61.2%
Yes
628
1,256

Panel B: Re-Estimation of Equation (1b) using Difference-in-Difference Specification
Test Sample
Prediction
Coeff.
t-stat.
β1
0.071
(0.49)
IFRS
β4
-0.023
(-0.63)
log(1+CompWeak)
β5
log(1+ CompStrong / (1+CompWeak))
-0.020*
(-1.81)
β6
IFRS×log(1+CompWeak)1
0.078**
(2.14)
1
β7
IFRS×log(1+ CompStrong / (1+CompWeak))
(-)
-0.094*** (-5.06)
R2
51.8%
Adjusted standard errors
Yes
# of fixed effects for matched pairs
493
# of observations
986

Control Sample
Coeff.
t-stat.
0.281***
(3.09)
0.161
(0.52)
-0.030
(-0.91)
-0.182***
(-4.69)
-0.057***
(-2.98)
62.3%
Yes
628
1,256

Prediction

(-)

Prediction

(-)

Difference
Coeff.
t-stat.
0.091
(0.91)
0.026
(1.63)
0.021
(1.25)

Difference
Coeff.
t-stat.
-0.210*
(-1.95)
-0.184*** (-4.36)
0.010
(0.56)
0.260***
(6.72)
-0.037**
(-1.82)

1

Note, for clarification, in the context of our difference-in-differences specification, the variable IFRS is just a time-period variable coded one (zero) for 2006 and 2007
(2003 and 2004). There are no IFRS-reporting firms in the control sample.
This table presents the coefficients of interest from our difference-in-differences estimates based upon Equations (1a) and (1b). For ease of exposition, the regression
coefficients for the control variables are untabulated. The sample used is a pooled sample that includes our mandatory adoption test sample (which is a matched sample
of IFRS-reporting IPOs from the period 2006-2007, and domestic GAAP-reporting IPOs from the period 2003-2004) from firms based in countries that mandated the
adoption of IFRS in 2005, and a control sample of IPOs from non-IFRS adoption countries, all of which report in domestic GAAP. The test and control samples are
pooled and each model is estimated with a dummy variable to distinguish between the test and control samples. Standard errors are clustered by country and month. We
report significance levels based upon one- (two-) tailed p-values for variables where we have (do not have) a directional prediction; 10%, 5%, and 1% are indicated by *,
**, and ***, respectively.

43
 
 

TABLE 6
Descriptive Statistics: Voluntary IFRS Adoption Sample
Panel A: IFRS-Reporting IPOs (N=34)
Mean
IniRet
25.5%
Comp
31.6
Proceeds
124.3
Partial Adjustment
0.00
Cross Listing
41.2%
Market Return
6.8%
Market Volatility
84.9%
#IPO
4.91
Secondary Market
29.4%
Common
55.9%
CompDomestic
10.6
IFRSdiff
25.6%
Leverage
0.340
ROA
7.8%
Multiple Acct Stds
47.1%

Min.

Q1

Median

Q3

Max.

-20.3%
2
0.2
-0.03
0
-58.6%
44.1%
0
0
0
0
0.0%
0.012
-36.6%
0

1.3%
11
5.9
0.00
0
-8.5%
58.0%
0
0
0
2
0.0%
0.193
0.5%
0

11.4%
22.5
16.0
0.00
0
4.1%
79.6%
3
0
1
3.5
9.5%
0.305
8.2%
0

43.4%
45
135.6
0.00
1
21.1%
105.0%
7
1
1
13
57.1%
0.502
17.6%
1

215.6%
99
569.3
0.03
1

Panel B: Domestic GAAP-Reporting IPOs (N=557)
IniRet
32.9%
-20.3%
Comp
25.0
1
Proceeds
43.4
0.2
Partial Adjustment
0.00
-0.03
Cross Listing
7.7%
0
Market Return
5.3%
-58.6%
Market Volatility
89.0%
40.5%
#IPO
8.59
0
Secondary Market
45.1%
0
Common
67.1%
0
CompDomestic
24.9
0
IFRSdiff
18.5%
0.0%
Leverage
0.317
0.012
ROA
1.3%
-83.4%
Multiple Acct Stds
41.8%
0

3.2%
6
5.0
0.00
0
-9.9%
59.7%
3
0
0
6
4.8%
0.185
-1.3%
0

14.2%
15
17.1
0.00
0
4.9%
84.9%
6
0
1
15
4.8%
0.308
6.2%
0

46.3%
40
38.5
0.00
0
22.0%
113.4%
13
1
1
39
42.9%
0.445
11.3%
1

215.6%
99
569.3
0.03
1
67.7%
191.1%
27
1
1
95
57.1%
0.689
30.4%
1

67.7%
191.1%
22
1
1
54
57.1%
0.684
30.4%
1

This table presents descriptive statistics for the voluntary adoption sample of 591 IPO firms that are used in the
analyses reported in Tables 7. This sample period is 2003-2004. Panel A (B) shows the descriptive statistics for the
34 (557) IFRS- (domestic GAAP-) reporting IPOs in the sample.
Variable Definitions (of variables not already defined in the endnotes of Table 3):
Common = A dummy variable equal to one (zero) for firms based in common (code) law countries.
IFRSdiff = The difference between IFRS and domestic GAAP of a country (Bae et al. 2008), scaled
by 21, the maximum number of possible differences between domestic GAAP and IFRS;
CompDomestic = The number of listed industry peers reporting in domestic GAAP;
Leverage = The natural logarithm of one plus the leverage ratio in the last fiscal year-end prior to the
IPO date;
ROA = Operating income scaled by total assets;

44 
 

Multiple Acct Stds = One if a firm is listed in a country that permits reporting in IFRS (e.g., China, Germany,
Poland, and Singapore) and zero otherwise.

45 
 

TABLE 7
Comparability and IPO Underpricing: Voluntary IFRS Adoption
Prob(IFRS) = Z’γ + ε;
IniRet = θ1 IFRS + θ2 log(1+Comp) + θ3 IFRS× log(1+Comp) + δ Inverse Mills Ratio + Controls + υ.

(2a)
(2b)

Panel A: Endogenous Treatment Model Results
Equation (2a)
Dep. Var. = Prob(IFRS)
Coeff.
z-stat.
IFRS
log(1+Comp)
IFRS×log(1+Comp)
Control Variables:
log(1+Proceeds)
Partial Adjustment
Cross Listing
Market Return
Market Volatility
log(1+#IPO)
IFRSdiff
Secondary Market
Common
log(1+CompDomestic)
IFRSdiff
log(1+Leverage)
ROA
Multiple Acct Stds
Inverse Mills Ratio

θ1
θ2
θ3

Predict

(-)
0.055

(0.76)

1.382***

(5.36)

0.287

(0.90)

-0.377***
1.737***
0.196
0.703
0.074

Equation (2b)
Dep. Var. = IniRet
Coeff.

z-stat.

0.350
0.010
-0.143**

(0.98)
(0.54)
(-1.69)

-0.064***
0.557
-0.008
0.063
0.254***
0.094***

(-4.49)
(0.20)
(0.10)
(0.90)
(4.45)
(3.47)

-0.179***
-0.281***

(-3.78)
(-5.26)

(-4.24)
(2.96)
(0.32)
(1.07)
(0.30)

δ

0.046

Year fixed-effects

Yes

Yes

# of observations

591

591

Panel B: Linear Combination Test (Eq. (2b)
(θ2 + θ3) = 0

-0.132*

(0.34)1

(-1.60)

1

The Inverse Mills Ratio is not statistically significant. One possibility is that, in this setting, there is no unobserved
determinant of IPO firms' choice of accounting standards that is omitted from the first-stage model that affects IPO
underpricing. This indicates that self-selection does not result in a significant bias in this OLS model.
This table presents the estimates of an endogenous treatment model, where Equation (2a), the first stage model, is a
binary response model, and Equation (2b), the second stage model, is a prediction model (Wooldridge, 2010). The
sample is composed of IPO firms that went public in 2003 and 2004 and chose to report in IFRS or domestic GAAP.
IniRet, the dependent variable, is the degree of IPO underpricing measured by the first trading-day return. IFRS is a
dummy variable coded one (zero) for an IPO firm that chooses to report in IFRS (domestic GAAP). Comp equals the
raw number of industry peers that use the same set of accounting standards as an IPO firm. We report significance
levels based upon one- (two-) tailed p-values for variables where we have (do not have) a directional prediction; 10%,
5%, and 1% are indicated by *, **, and ***, respectively.

46 
 

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