IAS VERSUS U.S. GAAP: INFORMATION ASYMMETRY-BASED EVIDENCE FROM GERMANY''''S NEW MARKET potx

Journal of Accounting Research
Vol. 41 No. 3 June 2003
Printed in U.S.A.
IAS Versus U.S. GAAP:
Information Asymmetry–Based
Evidence from Germany’s
New Market
CHRISTIAN LEUZ
∗
Received 3 October 2001; accepted 7 November 2002
ABSTRACT
Motivated by the debate about globally uniform accounting standards, this
study investigates whetherfirms usingU.S. generally accepted accounting prin-
ciples (GAAP) vis-`a-vis international accounting standards (IAS) exhibit dif-
ferences in several proxies for information asymmetry. It exploits a unique
setting in which the two sets of standards are put on a level playing field. Firms
trading in Germany’s New Market must choose between IAS and U.S. GAAP
for financial reporting, but face the same regulatory environment otherwise.
Thus, institutional factors such as listing requirements, market microstruc-
ture, and standards enforcement are held constant. In this setting, differences
in the bid-ask spread and share turnover between IAS and U.S. GAAP firms
are statistically insignificant and economically small. Subsequent analyses of
∗
University of Pennsylvania. I gratefully acknowledge helpful comments from Anne d’Arcy,
George Benston, Phil Berger, Gus De Franco, Robert Holthausen, Peter Knutson, Christian
Laux, S. P. Kothari, Claudia R¨oder, Robert Verrecchia, and especially Ray Ball and the anony-
mous referee. This paper has benefited from presentations at the American Enterprise Insti-
tute, University of California at Berkeley, Columbia University, Harvard University, J. W. Goethe
Universit¨at Frankfurt, MIT, University of Michigan, Stanford University, Tilburg University, the
EAA Meetings (Munich) and the EFA Meetings (Barcelona). I would also like to thank Uwe
Schweickert (Deutsche B¨orse), Peter Gomber (Deutsche B¨orse), J¨org Hueber (KPMG), Rainer

J¨ager (PWC), and IBES for generously providing data for this study, and Tobias Herwig for his
excellent research assistance. I also gratefully acknowledge financial support by the Wharton
Electronic Business Initiative (WeBI).
445
Copyright
C

, University of Chicago on behalf of the Institute of Professional Accounting, 2003
446 C. LEUZ
analysts’ forecast dispersion, initial public offering underpricing, and firms’
standard choices corroborate these findings. Thus, at least for New Market
firms, the choice between IAS and U.S. GAAP appears to be of little conse-
quence for information asymmetry and market liquidity. These findings do
not support widespread claims that U.S. GAAP produce financial statements
of higher informational quality than IAS.
1. Introduction
This study is motivated by the debate about the two leading contenders in
the global competition among financial reporting regimes: U.S. generally
accepted accounting principles (GAAP) and international accounting stan-
dards (IAS). This debate, which is summarized in section 2, focuses primarily
on comparisons of the stipulated accounting methods per se. There is, how-
ever, little empirical evidence on the standards’ economic consequences in
capital markets (see also Pownall and Schipper [1999]).
In this article I investigate whether firms using U.S. GAAP vis-`a-vis IAS
exhibit cross-sectional differences in several proxies for information asym-
metry, such as bid-ask spreads and share turnover. I focus on these proxies
because reducing information asymmetries and increasing market liquidity
is one, albeit an important, concern in securities and accounting regulation
(e.g., Loss and Seligman [2001]). Moreover, in using these proxies, the tests
are not restricted to comparisons of summary accounting measures such as

earnings but capture differences in financial reporting information more
broadly (e.g., footnote disclosures).
The study exploits a unique setting in which the two competing sets of stan-
dards are placed on a level playing field. Firms trading in Germany’s New
Market are required to choose between IAS and U.S. GAAP for financial
reporting purposes, but face the same regulatory environment otherwise.
Potentially offsetting institutional factors such as capital market structure,
listing requirements, and enforcement of accounting standards are held
constant. I thereby avoid difficulties of comparisons across firms from differ-
ent countries or different capital markets (e.g., Frost and Pownall [1994]).
Furthermore, consolidated IAS and U.S. GAAP reports are neither the basis
of taxation nor dividend restrictions in company law, focusing the compar-
ison on disclosure effects in capital markets.
The results indicate that the differences in the bid-ask spread and share
turnover across IAS and U.S. GAAP firms are statistically insignificant and
economically small. For instance, the spread regressions suggest that, set-
ting statistical significance aside, the effect of U.S. GAAP reporting is less
than 3% of the percentage spread. Next, I examine analysts’ forecast disper-
sion and initial public offering (IPO) underpricing as alternative proxies
for information asymmetry and find that the differences are also statisti-
cally insignificant. Finally, I analyze firms’ standard choices and check for
selection bias with two-stage regressions. These tests corroborate the other
findings. In summary, the choice of IAS or U.S. GAAP appears to be of little
consequence for information asymmetry and market liquidity.
IAS VERSUS US. GAAP 447
This finding is open to at least two interpretations. If accounting stan-
dards are important in determining firms’ accounting quality (e.g., Levitt
[1998]), this finding implies that IAS and U.S. GAAP are comparable sets
of standards, at least in terms of their ability to reduce information asym-
metries. The evidence does not support claims that U.S. GAAP produce

financial statements of higher informational quality than IAS.
However, the finding is also consistent with the view that accounting qual-
ity is largely determined by firms’ reporting incentives created by market
forces and institutional factors rather than by accounting standards (in par-
ticular, Ball, Robin, and Wu [Forthcoming], Ball and Shivakumar [2002]).
Based on this view, IAS and U.S. GAAP firms in the New Market are ex-
pected to exhibit similar accounting quality, despite differences in the stan-
dards, because they face similar market forces and institutional factors.
Thus, in holding institutional factors constant and varying firms’ standards,
this study complements other studies that vary firms’ incentives while hold-
ing standards constant (e.g., Ball, Robin, and Wu [Forthcoming], Ball and
Shivakumar [2002]). Together, the studies provide evidence suggesting that
the global accounting debate focuses too much on the standards choice and
too little on market forces and institutional factors, as also argued by Ball
[2001].
Although the New Market setting offers several advantages, there are
caveats that should be borne in mind when interpreting the results. First,
New Market firms are young growth firms that are strongly dependent on
equity financing. Although information asymmetry and disclosure issues are
pertinent for such firms (Smith and Watts [1992]), financial statements (of
any kind) may not be as important or serve special purposes, reducing the
power of my tests. Moreover, it is unclear whether the findings generalize to
firms that, for instance, are in more mature industries, have higher leverage,
or trade on other exchanges.
Second, the study focuses on a comparison of IAS and U.S. GAAP in terms
of information asymmetry in the equity market and hence is limited in scope.
There are other important roles of accounting and disclosure standards,
such as improving corporate governance, which are not considered in this
study. Third, New Market firms choose their accounting standards. Thus,
my results are only valid to the extent that I have appropriately controlled

for selection bias. Finally, the paper does not address the policy question of
whether a country should accept or switch to IAS.
1
The remainder of the paper is organized as follows. Section 2 sketches
the global accounting debate and summarizes prior empirical results.
Section 3 describes Germany’s New Market. Section 4 delineates the re-
search design and section 5 presents the results for bid-ask spreads and share
turnover. Section 6 considers alternative information asymmetry proxies and
1
See, for example, Pownall and Schipper [1999], Dye and Sunder [2001], and Sunder
[2002] for this debate. Note also that Holthausen and Watts [2001] and Ronen [2001] caution
about drawing policy implications from market-based tests.
448 C. LEUZ
section 7 examines determinants of firms’ standard choices. Section 8 con-
cludes the paper.
2. The Development of IAS, the Global Accounting Debate,
and Prior Evidence
The International Accounting Standards Committee (IASC) was
founded in 1973 to set international accounting standards and promote
their global acceptance. In response to criticism of its early standards, the
IASC embarked on the Comparability/Improvements Project in 1987. The
revised standards, which became effective in 1995, substantially reduced
the number of accounting choices. In July 1995, the IASC and International
Organization of Securities Commissions (IOSCO) agreed on a list of ac-
counting issues that needed to be addressed by any set of standards seeking
IOSCO’s endorsement for cross-border offerings and listings. The ensuing
Core Standards Project led to substantial revisions of IAS. By March 1999,
the IASC completed all but one of those issues and subsequently received
IOSCO’s endorsement subject to “reconciliation, disclosure and interpreta-
tion at the national level” (IOSCO Press Release [May 17, 2000]).

These developments and the competition between IAS and U.S. GAAP to
become the global set of accounting standards have led to a debate about
their relative quality. Since then, several security regulators such as the U.S.
Securities and Exchange Commission (SEC) and the Canadian Securities
Administrators (CSA) have asked for feedback on the quality of IAS (e.g.,
SEC [2000], CSA [2002]).
In the ongoing debate, IAS proponents argue that IAS have improved
substantially over the years and that revised IAS are relatively close to U.S.
GAAP with minor differences remaining.
2
For instance, Harris [1995] con-
ducts a detailed case study computing earnings and shareholders’ equity
for eight companies under both standards. He concludes that firms com-
plying with revised IAS provide accounting measures that are essentially
consistent with U.S. GAAP and that, based on his study, there is no com-
pelling evidence that U.S. GAAP are superior to IAS. Others point out that
disclosures are sufficient to allow investors to make their own inferences in
those instances where substantial differences remain or IAS permit several
accounting choices (e.g., Enevoldsen, Jones, and Carsberg [2000]).
Overall, the proponents claim that IAS are now of sufficiently high quality.
Consistent with this opinion, a recent survey by KPMG [2000] shows that
CFOs of large European corporations view IAS as offering similar quality
while being cheaper to implement than U.S. GAAP, which are often per-
ceived as being too detailed and too complex.
IAS opponents, although acknowledging that IAS have improved consid-
erably, argue that many important differences between the two standards
2
See, for example, E. MacDonald, “U.S. Firms Likely to Balk at SEC Move to Ease Listing of
Foreign Companies,” Wall Street Journal, February 18, 2000, p. A3.
IAS VERSUS US. GAAP 449

remain and that U.S. GAAP are still superior because IAS are less rigorous,
are less detailed, afford more flexibility, or require fewer disclosures.
3
The
Financial Accounting Standards Board (FASB [1999]), for instance, points
to more than 250 key differences in four categories: recognition, measure-
ment, permissible alternatives, and lack of requirements or guidance.
4
Based
on this comparison, the FASB concludes that IAS are of lower quality than
U.S. GAAP.
5
In summary, there are opposing views on the quality of IAS relative to
U.S. GAAP, but the debate focuses on the stipulated accounting methods
themselves rather than any empirical evidence. Prior studies focus largely on
comparing foreign and U.S. GAAP financial statements, for instance, with
respect to the value relevance of accounting earnings (e.g., Alford et al.
[1993]). Other studies use Form 20-F reconciliations to assess the compara-
bility and quality of foreign GAAP relative to U.S. GAAP (e.g., Amir, Harris,
and Venuti [1993]). Using an information-asymmetry approach, which en-
compasses a broad set of disclosures, Leuz and Verrecchia [2000] compare
German firms following U.S. GAAP or IAS with firms following German
GAAP.
A few studies explicitly address the relative quality of IAS and U.S. GAAP
and hence are particularly pertinent to the current debate on global ac-
counting standards. Harris and Muller [1999] examine Form 20-F recon-
ciliations from IAS to U.S. GAAP. They find that, based on reconciliation
magnitudes, IAS are closer to U.S. GAAP than other foreign GAAP but that
reconciliation items are incrementally value relevant.
6

They interpret their
findings as evidence that IAS and U.S. GAAP accounting measures are not
substitutes. However, as Pownall and Schipper [1999] point out, evidence
from 20-F reconciliations is unlikely to be representative of IAS (or foreign
GAAP) firms not seeking U.S. listings.
7
Ashbaugh and Olsson [2002] ex-
amine non-U.S. firms quoted on London’s SEAQ. They find that IAS and
U.S. GAAP earnings and book values of equity are equally value relevant
but that the relative value relevance depends on the valuation model used.
Although these results are consistent with my findings, the tests are based on
3
See, for example, E. MacDonald, “U.S. Accounting Board Faults Global Rules,” Wall Street
Journal, October 18, 1999, p. A1; L. Berton, “Countdown to Harmonization,” Institutional In-
vestor, June 1999, pp. 25–26; J. Garten, “Global Accounting Rules? Not So Fast,” Business Week,
April 5, 1999, p. 26; M. McNamee, “Can the SEC Make Foreign Companies Play by Its Rules?”
Business Week, March 6, 2000, p. 46; G. Imhoff, “Compromising Standards Threatens Capital-
ism,” The Dividend, Spring 1999, pp. 22–25.
4
The International Forum on Accountancy Development (www.ifad.net) provides updated
comparisons.
5
See E. MacDonald, “U.S. Accounting Board Faults Global Rules,” Wall Street Journal, Octo-
ber 18, 1999, p. A1.
6
Davis-Friday and Rueschhoff [2001] examine seven firms before and after the IASC’s Com-
parability Project and find that IAS net income and shareholders’ equity are more significantly
related to market value after the revision of IAS.
7
Besides, prior research provides little evidence that investors actually use Form 20-F rec-

onciliations. See Saudagaran and Meek [1997] for a discussion.
450 C. LEUZ
a small sample of firms, most of which are also traded in the United States
and hence do not control for potentially confounding listing, enforcement,
or other institutional effects. Moreover, the tests focus solely on summary
accounting measures and hence do not account for footnote disclosures
that may compensate for recognition differences.
Finally, several recent studies find that accounting quality is determined
primarily by market forces and institutional factors, rather than account-
ing standards (e.g., Ball, Robin, and Wu [Forthcoming], Leuz, Nanda, and
Wysocki [Forthcoming]). These findings suggest that standards per se do
not have a major impact on accounting quality and that the global account-
ing debate focuses perhaps too much on the standards.
Thus, based on the prior literature, the economic substance of the differ-
ences between IAS and U.S. GAAP remains an open and largely empirical
question.
3. The New Market in Germany
The New Market (or Neue Markt) was launched in March 1997 as a new
German stock market segment geared toward small- and medium-size com-
panies in innovative and fast-growing industries. Within a few months of
its inception, it became Europe’s most successful equity market for growth
firms, both in terms of market capitalization and number of listings.
8
How-
ever, along with other growth and technology markets, the New Market suf-
fered a severe downturn in recent years. Responding to this market trend,
Deutsche B¨orse decided to reorganize its markets and stop singling out
growth and technology stocks in a segment. In 2003, New Market firms are
being reassigned to two newly created market segments, called Prime and
General Standard. The Prime Standard segment inherits the strict listing

and disclosure requirements of the New Market, which go substantially be-
yond those of the General Standard.
9
In addition, new securities regulation
is under way to address enforcement problems that have become apparent
during the New Market period.
10
8
See, for example,“European Stockmarkets: A German Coup,” The Economist, January 9,
1999, pp. 69–71; R. Zimmermann, “Eine Flasche Champagner zum dritten Geburtstag,” Finan-
cial Times Deutschland, March 9, 2000, p. 20; “Amerikas Anleger werden vielf¨altig gesch¨utzt,”
Frankfurter Allgemeine Zeitung , Septermber 5, 2001, p. 208; “Neuer Markt,” Frankfurter Allgemeine
Zeitung (Supplement), March 6, 2001.
9
See “Neuer Markt Closure, Comment & Analysis,” Financial Times, September 27, 2002,
p. 11.
10
The Deutsche B¨orse tightened the rules several times to address problems as they became
apparent. For instance, in March 2001, it introduced rules that (1) require disclosure of all
share transactions by managers, board members, and the company itself; (2) standardize and
extend quarterly financial reports; and (3) increase penalties for rule violations, including fines
up to 100,000 EUR and delisting. See A. Kueppers, “Following in the Shadow of Nasdaq, Neuer
Markt Sees 76% Plunge in its Stocks,” Wall Street Journal, March 20, 2001, p. C10; S. Ascarelli,
“German Exchange Unplugs Neuer Markt,” Wall Street Journal, September 27, 2002, p. A12.
IAS VERSUS US. GAAP 451
The New Market’s rules were deliberately chosen to exceed traditional
German listing and disclosure requirements because New Market firms are
characterized by substantial uncertainty about business prospects and man-
agement expertise.
11

To describe briefly the key rules, the New Market’s
Regelwerk stipulates that, at the IPO, firms are three years of age, have a min-
imum free float of 20%, and commit to a six-month lock-up period.
12
There
are extensive and detailed disclosure requirements for the IPO prospectus
(Regelwerk, §4). In particular, firms have to provide comparable financial
statements for three previous fiscal years. Subsequently, firms have to pre-
pare and publish annual financial statements no later than three months
after the fiscal year end (Regelwerk, §7). Financial statements have to be in
accordance with either IAS or U.S. GAAP. In addition, firms must publish
quarterly reports within two months after each quarter and hold at least one
analyst conference per year.
The Regelwerk also requires that annual financial statements be audited.
The enforcement of either IAS or U.S. GAAP lies primarily with the auditors,
whose legal liability has increased considerably since the amendment of
§323 HGB (German Commercial Code) in April 1998. In addition, auditors
and directors could face criminal prosecution for misleading or fraudulent
financial statements (§§331 and 332 HGB). It is also possible to sue for
damages in civil courts, but only after a conviction in criminal proceedings.
However, as U.S style shareholder litigation or SEC-like monitoring does not
exist in Germany, enforcement is unlikely to be as strong as in the United
States. For this reason, I exclude New Market firms with U.S. listings from
the sample. The concern is that differential enforcement could otherwise
bias the tests. However, I note that weak enforcement likely reduces the
power of my tests.
Mitigating this concern, Glaum and Street [Forthcoming] find that the
compliance of New Market firms with required disclosures is on average
reasonably high.
13

They also show that firms with U.S. listings exhibit higher
compliance levels than do firms without such listings. However, once this
effect is controlled for, the compliance levels of IAS firms are only slightly
lower (≈2%) and only marginally significant (at the 8% to 9% level).
14
Thus,
any remaining bias in my tests appears to be small and in favor of U.S. GAAP
firms.
Finally, as my empirical tests are based on bid-ask spreads and share
turnover, I briefly describe the market microstructure of the New Market.
11
See, for example, V. Fuhrmans, “Playing by the Rules: How Neuer Markt Gets Respect,”
Wall Street Journal, August 21, 2000, p. A3; “Strenges Regelwerk sorgt f ¨ur hohe Transparenz am
Neuen Markt,” Frankfurter Allgemeine Zeitung , September 25, 2000, p. 32.
12
The Regelwerk is available online at />13
Mean and median compliance ratios are 83.7% and 85.9%, respectively. Bradshaw and
Miller [2002] show that, even for U.S. firms, compliance ratios are on average below 100%.
But the compliance ratios are not directly comparable.
14
D’Arcy and Grabensberger [Forthcoming] find similar results comparing the compliance
of IAS and U.S. GAAP firms with the New Market’s quarterly reporting rules.
452 C. LEUZ
Shares are traded simultaneously on the floor and on an electronic trading
platform (Xetra). Floor trading is organized as an auction system only. The
electronic trading system, which is a hybrid between an auction and market-
maker system, allows traders to post limit orders. Spreads arise from the best
bid and best ask of all limit orders, not just the quotes of the market makers.
Each New Market firm has to name at least two designated sponsors
(Betreuer) that act as market makers and promote liquidity. They provide

binding bid and ask limit orders (or quotes) for the three daily auctions and
upon request by a market participant (with a maximum response time of
120 seconds).
15
The sponsors’ minimum quote volume is 20,000 EUR and
their quoted spreads must not exceed 4%. The exchange monitors spon-
sor performance (since October 1999) and publish ratings (since January
2000). Prior studies suggest that sponsors have a stabilizing, but not domi-
nating, role in the New Market, and in particular they facilitate larger trades
(Theissen [1998], Gerke and Bosch [1999]).
4. Research Design and Information Asymmetry Proxies
Economic theory suggests that information asymmetries between poten-
tial buyers and sellers of firm shares introduce adverse selection into sec-
ondary share markets and hence reduce market liquidity (e.g., Copeland
and Galai [1983], Glosten and Milgrom [1985]). Information asymmetries
are costly to firms, as investors adjust prices to compensate for holding
shares in illiquid markets. Increasing the level or precision of disclosure
should reduce the likelihood of information asymmetries between investors
and increase market liquidity (e.g., Diamond and Verrecchia [1991]). Thus,
information asymmetry proxies should reflect, among other things, firms’
accounting quality. In principle, the measures can capture any difference
between IAS and U.S. GAAP and should account for trade-offs among recog-
nition, measurement, and footnote disclosures. Consistent with these hy-
potheses, Welker [1995], Healy, Hutton, and Palepu [1999], and Leuz and
Verrecchia [2000] provide evidence that information asymmetry and liquid-
ity proxies are associated with firms’ disclosure and accounting policies.
Furthermore, security market regulators emphasize the role of high-
quality accounting standards in leveling the playing field among investors
and increasing investor confidence, that is, in reducing information asym-
metries and increasing liquidity (e.g., Sutton [1997]). For instance, Levitt

[1998, p. 81] states, “High[er] quality accounting standards result in greater
investor confidence, which improves liquidity, [and] reduces capital costs”
(see also FASB [1999, p. 3]).
The preceding discussion suggests information asymmetry–based tests as a
way to assess the economic substance of the global accounting debate and, in
particular, the arguments put forth in favor of U.S. GAAP. The tests examine
whether, ceteris paribus, firms employing U.S. GAAP exhibit less information
15
For details, see Designated Sponsor Guide, />IAS VERSUS US. GAAP 453
asymmetry and higher market liquidity than firms using IAS. If the differ-
ences between IAS and U.S. GAAP firms turn out to be insignificant, then
either IAS and U.S. GAAP are comparable in reducing information asym-
metries, consistent with the argument of IAS proponents, or standards do
not primarily determine informational quality, as suggested by Ball, Robin,
and Wu [Forthcoming].
16
As the ceteris paribus condition is critical for the test, I examine New Mar-
ket firms that are incorporated in Germany and that do not trade abroad.
For these firms, country- and market-specific factors, such as the enforce-
ment of accounting standards and nonaccounting disclosure requirements,
are held constant. Furthermore, consolidated IAS or U.S. GAAP reports do
not have immediate tax or dividend implications. In Germany, taxation and
legal dividend restrictions are not based on consolidated (or group) finan-
cial statements. Under the Commercial Code, such statements serve purely
informational purposes.
I analyze whether IAS and U.S. GAAP firms in the New Market exhibit
cross-sectional differences in the bid-ask spread and share turnover, both of
which are standard proxies for information asymmetry and market liquidity.
Although spread data are not readily available for the New Market, the
Deutsche B¨orse kindly provided data from June 1, 1999, to July 31, 1999,

and from June 1, 2000, to August 31, 2000. In 1999, the spreads are measured
after the New Market All Share index had gained 24% from January to the
end of May. In 2000, it had lost almost 35% from its peak in March to the
beginning of the measurement interval. Analyzing both periods serves as
a robustness check that the results are not specific to the New Market’s
boom phase. However, sharp market movements, such as those of the New
Market in 1999 and 2000, could also make the proxies more cross-correlated
and less powerful for my purposes because investors are more likely to rely
on marketwide information rather than firm-specific information in these
times.
17
It is therefore noteworthy that the measurement intervals themselves
are comparatively stable periods, where the New Market All Share index
posted only modest returns of 1.8% and 1.3%, respectively.
For each stock, the exchange provides an equally weighted monthly av-
erage of all spreads that existed in the electronic trading system (Xetra).
18
The aggregated data provision precludes a decomposition of the spread into
components related and unrelated to information asymmetry. There are,
however, several institutional features that mitigate this data limitation and
make the Xetra spreads used in this study conceptually appealing proxies for
16
These arguments presume that test power is sufficiently high. The power issue is therefore
explicitly addressed in the robustness checks and should be kept in mind as a caveat when
interpreting the results.
17
I thank the anonymous referee for pointing this out.
18
Every (new) spread arising from either a change of the best-bid or the best-ask price is
recorded. In 2000, the monthly average for each stock is computed on average from more than

3,000 individual spreads.
454 C. LEUZ
information asymmetry.
19
First, spreads arise from limit orders posted in the
electronic trading system by all traders, instead of the quotes of a specialist or
a few market makers. In such a market, other spread components unrelated
to information asymmetry, such as inventory-holding costs or monopoly
rents, should be smaller. Empirical comparisons of order- and quote-driven
markets support this conjecture (e.g., Huang and Stoll [1996]). Second,
traders are charged for order processing separately, and New Market firms
pay fees to their designated sponsors to compensate them for their service.
For these reasons, order-processing costs are unlikely to be a major spread
component. Third, trades are executed automatically, which implies that the
quoted spreads are the effective spreads. Finally, share prices are quoted with
two decimal places, which reduces price discreteness and should increase
the power of the proxy.
Similar issues arise with respect to share turnover. Although adverse selec-
tion among investors clearly reduces liquidity, the proxy also reflects factors
unrelated to information asymmetry, such as portfolio rebalancing, liquidity
shocks, or changes in risk preferences. There is, however, evidence that sup-
ports the choice of turnover as an inverse proxy for information asymmetry.
For instance, Easley et al. [1996] show that the probability of informed trad-
ing is decreasing in trading volume and Grammig, Schiereck, and Theissen
[2000] confirm their findings for the regular German market segment.
5. Cross-Sectional Analysis of Information Asymmetry
and Market Liquidity
5.1 SAMPLE SELECTION AND DESCRIPTIVE STATISTICS
As of April 30, 1999, 90 firms were listed in the New Market. I eliminate
firms that are incorporated outside of Germany (6), listed abroad (5), or

both (5). This restriction reduces the sample to 74 firms but ensures that
all of them trade in the same market and operate in the same legal envi-
ronment.
20
In addition, I eliminate 5 firms that follow German GAAP in
their annual reports.
21
Thus, the final sample for 1999 contains 69 firms. To
increase the sample, I also perform my analyses using the 246 firms listed
in the New Market as of April 30, 2000. Again, I eliminate firms that are
19
Besides, Clarke and Shastri [2000] demonstrate severe problems with the decomposition of
spreads. Thus, it is not obvious whether the decomposition increases or decreases measurement
error.
20
Some New Market firms are also listed on the Geregelten Markt of regional exchanges
or traded in the Freiverkehr (OTC market). However, the disclosure and listing requirement
for these market segments are limited compared with the New Market. Moreover, a listing on
the New Market entails a private contract with the Deutsche B¨orse and a registration for the
Geregelten Markt in Frankfurt.
21
In its early days, the New Market allowed some firms to provide German GAAP financial
statements for a limited time if they were temporarily unable to prepare them according to
IAS or U.S. GAAP. By April 30, 2000, all firms follow either IAS or U.S. GAAP in their annual
reports.
IAS VERSUS US. GAAP 455
TABLE 1
Descriptive Statistics on Accounting Standard Choices
Panel A: Accounting standard choices in the New Market
a

All Firms Listed as Sample for 1999 All Firms Listed as Sample for 2000
of April 30, 1999 (n = 69 firms) of April 30, 2000 (n = 195 firms)
IAS 42 40 117 102
US GAAP 43 29 129 93
Panel B: Distribution of accounting standards by industry
b
Sample for 1999 Sample for 2000
IAS U.S. GAAP IAS U.S. GAAP
Bio- and Med-Technology 1 1 6 7
Industrials & Industrial Services 4 3 6 3
Internet 3 6 15 28
IT Services 1 4 14 12
Media & Entertainment 7 2 17 9
Software 10 3 18 12
Technology 10 8 20 16
Telecommunications 4 2 6 6
a
As of April 30, 1999, 90 firms were listed in the New Market. Five of them follow German GAAP for
their 1998 annual report and hence are excluded (see footnote 21). Thus, the first column comprises 85
firms. The sample for 1999 (second column) excludes firms that are incorporated outside Germany and/or
are listed on a foreign exchange. The third column comprises all 246 firms listed in the New Market as of
April 30, 2000. The sample for 2000 (last column) excludes firms that are incorporated outside Germany
and/or are listed on a foreign exchange.
b
Panel B is based on the industry classification provided for the New Market by the Deutsche B¨orse
().
incorporated outside Germany (34), listed abroad (11), or both (6). Thus,
the final sample for 2000 comprises 195 firms.
Panel A of table 1 reports the accounting standard choices of sample firms
and all New Market firms as of April 30, 1999, and April 30, 2000. The panel

shows that IAS and U.S. GAAP are fairly evenly distributed across firms. The
percentage of U.S. GAAP firms is smaller in my samples than in the entire
market because firms that are eliminated because of their foreign listing
often trade in the U.S. and use U.S. GAAP. Panel B reports firms’ standard
choices by industry. Both standards are fairly evenly distributed within most
industries, except in Media & Entertainment and in Internet industries,
where firms seem to prefer IAS and U.S. GAAP, respectively. Subsequent
tests therefore check for industry effects.
Table 2 provides descriptive statistics for the dependent variables and firm
characteristics by accounting standard choice. The table reports the average
percentage spread from June 1, 1999, to July 31, 1999, from June 1, 2000,
to August 31, 2000, respectively, and the median daily share turnover from
May 1, 1999, to July 31, 1999, and from June 1, 2000, to August 31, 2000,
respectively.
22
I use the median turnover because the median is conceptually
a better proxy for the (normal) level of liquidity trading than the average,
22
Although the exchange provides spread data in 1999 for two months only, I use three-
month intervals for all other variables to have at least 60 trading days to compute them.
456 C. LEUZ
TABLE 2
Descriptive Statistics for the Dependent Variables and Firm Characteristics
1999 2000
Variable Reporting Number Mean Median Number Mean Median
Bid-ask IAS 40 2.333 2.302 102 1.751 1.751
spread U.S. GAAP 29 2.149 2.197 93 1.693 1.778
ALL 69 2.256 2.266 195 1.723 1.754
Share IAS 40 0.839 0.734 102 0.098 0.071
turnover U.S. GAAP 29 0.761 0.756 93 0.084 0.072

ALL 69 0.806 0.741 195 0.092 0.072
Market IAS 40 498.005 204.510
∗
102 497.318 177.943
∗
capitalization U.S. GAAP 29 545.883 357.616 93 973.257 287.758
ALL 69 518.128 211.128 195 724.304 223.750
Share price IAS 40 0.036 0.035 102 0.042 0.039
volatility U.S. GAAP 29 0.035 0.037 93 0.043 0.042
ALL 69 0.036 0.035 195 0.042 0.040
Free float IAS 40 0.395
∗
0.381
∗∗
102 0.366
∗∗
0.333
∗∗∗
U.S. GAAP 29 0.335 0.296 93 0.324 0.296
ALL 69 0.370 0.344 195 0.346 0.320
Days listed in IAS 40 297.250 260.500 102 398.157
∗
344.000
∗
New Market U.S. GAAP 29 256.000 257.000 93 333.882 306.000
ALL 69 279.913 257.000 195 367.503 329.000
Analyst IAS 40 4.125 3.000 102 3.539 3.000
following U.S. GAAP 29 4.103 3.000 93 3.570 3.000
ALL 69 4.116 3.000 195 3.554 3.000
Forecast IAS 15 0.251 0.130 74 0.224 0.170

dispersion U.S. GAAP 12 0.259 0.100 54 0.207 0.125
ALL 27 0.254 0.130 128 0.217 0.150
The samples for 1999 and 2000 comprise all firms listed in the New Market as of April 30, 1999, and
April 30, 2000, respectively, excluding those that still follow German GAAP, are incorporated outside of
Germany, and/or are listed on a foreign exchange (see table 1 for details). Spread data have been provided
by Deutsche B¨orse. The spread is expressed as a percentage and computed as the difference between the
best bid and ask divided by the midpoint. For each stock, the exchange provides a monthly average of all
spreads that existed in the electronic XETRA trading system (see discussion in section 4). The table reports
the average percentage spreads from June 1, 1999, to July 31, 1999, and from June 1, 2000, to August 31,
2000. Turnover, share price, and market value data have been obtained from Datastream. Share turnover is
expressed as a percentage and computed for 60 trading days as the median of daily volume in Euro divided
by daily market capitalization in Euro from May 1, 1999, to July 31, 1999, and from June 1, 2000, to August
31, 2000, respectively. The market capitalization (in millions of Euro) is measured as the average market
value of equity from May 1, 1999, to July 31, 1999, and from June 1, 2000, to August 31, 2000, respectively.
Share price volatility is computed over the same intervals as the standard deviation of daily returns. Free float
(i.e., 1 minus the percentage of shares closely held) was obtained from B¨orse Online (based on ownership
data published by New Market firms) and is measured as of May 1, 1999, and June 1, 2000, respectively.
The number of days listed in the New Market is measured from the IPO to April 30, 1999, and April 30,
2000, respectively. Analyst following (i.e., the number of financial analysts providing earnings forecasts) was
obtained from IBES. Forecast dispersion is the standard deviation of the seven-month consensus forecast
for the fiscal years 1999 and 2000. Asterisks indicate that the means (medians) of IAS and U.S. GAAP firms
are significantly different using a two-tailed t-test (Mann-Whitney-Wilcoxon test).
∗
p < .1;
∗∗
p < .05;
∗∗∗
p < .01.
which may be influenced by a few days of heavy trading around a particular
event. Using the average turnover, however, produces similar results.

The descriptive statistics show that the New Market’s average spread and
average share turnover are considerably lower in 2000 than in 1999. The
sharp decline in share turnover likely reflects the end of the new economy
IAS VERSUS US. GAAP 457
boom and the market downturn. Continuous efforts of Deutsche B¨orse to
improve market structure and trading efficiency could explain the reduction
in spreads. For instance, as described in section 3, the Deutsche B¨orse started
monitoring sponsor performance in October 1999 and publishing sponsor
ratings in January 2000, which could have reduced the average spread in
the market. As marketwide fluctuations in liquidity and microstructure im-
provements apply to all firms, they are unlikely to affect my cross-sectional
tests.
23
The differences in the spread and share turnover across U.S. GAAP and
IAS firms are small and statistically insignificant for both the groups’ means
and medians. But as these univariate comparisons do not control for spread
and turnover determinants, they should be interpreted cautiously. Table 2
also presents descriptive statistics for other firm characteristics, showing that
the two groups exhibit significant differences in firm size (medians only)
and free float.
5.2 REGRESSION ANALYSIS
In this section I study cross-sectional differences in the bid-ask spread
and share turnover between IAS and U.S. GAAP firms controlling for firm
characteristics. I report the results for 1999 and 2000 using the samples
described in the previous section.
5.2.1. Bid-Ask Spreads. The bid-ask spread model is based on the extant
literature. Prior studies suggest that the percentage spread is negatively asso-
ciated with trading volume, firm size, and market-maker competition, and
positively associated with price volatility and insider presence (e.g., Stoll
[1978], Chiang and Venkatesh [1988], Glosten and Harris [1988]).

To control for these determinants, I use the average share turnover, aver-
age market capitalization, and daily share price volatility over the respective
intervals in 1999 and 2000.
24
I also include the firm’s free float as an in-
verse proxy for the presence of insiders. Reflecting the New Market’s order-
driven microstructure, the model does not include a variable for market-
maker competition.
25
To conduct the test developed in the previous section,
23
The fact that spreads and turnover move in the same direction appears to send mixed
signals about changes in (aggregate) liquidity. Although both proxies are related to the same
economic construct, they are also affected by other factors unrelated to information asymmetry
(see section 4). As these factors are unlikely to be the same for spreads and turnover, it is
conceivable that changes in these other factors are responsible for the joint decrease in spreads
and turnover (see also Chordia, Roll, and Subrahmanyam [2001]).
24
See table 2 for details. Turnover is used as opposed to unscaled trading volume to avoid
multicollinearity problems with market capitalization.
25
In an earlier version, I reported spread regressions including the number of designated
sponsors as a control variable. These regressions are close to those in table 3 and yield an
insignificant coefficient for the number of designated sponsors. The latter finding is not sur-
prising considering that spreads arise from limit orders posted by all traders, and not only
the from market-maker quotes (see also the discussion in section 4). Similarly, controlling for
sponsor ratings does not materially affect results.
458 C. LEUZ
I introduce a binary variable into the model indicating the firm’s reporting
choice (U.S. GAAP = 1). To the extent that U.S. GAAP firms report higher

quality information, the dummy variable is expected to exhibit a negative co-
efficient indicating lower spreads and hence lower information asymmetry
for U.S. GAAP firms.
As most analytical models identify multiplicative relations between the
spread and its determinants (e.g., Stoll [1978], Glosten and Milgrom
[1985]), I estimate a log-linear specification, which is standard in the ex-
tant literature.
26
Spearman correlations and regression diagnostics based
on Belsley, Kuh, and Welsch [1980] suggest that multicollinearity among
the independent variables is not a problem.
Panel A of table 3 presents the coefficients and t-statistics for ordinary
least squares (OLS) regressions with White-corrected standard errors. The
regressions explain at least 75% of the variation in spreads, which is com-
parable to prior research. In both years, the coefficient on the U.S. GAAP
dummy is negative, but not statistically significant. All other variables have
the expected signs and are highly significant.
In summary, there is little evidence that firms employing U.S. GAAP have
lower bid-ask spreads than firms using IAS. Thus, the regressions do not
support the claim that U.S. GAAP are of significantly higher quality than
IAS.
5.2.2. Share Turnover. The turnover model is also based on the extant
literature. Prior studies suggest that share turnover is related to firm size and
positively associated with volatility, institutional ownership, and the inclusion
in a stock index (e.g., Bessembinder, Chan, and Seguin [1996], Tkac [1999],
Leuz and Verrecchia [2000]).
To control for these determinants, I use the average market capitaliza-
tion and daily share price volatility over the respective intervals in 1999 and
2000, and a binary variable indicating whether the firm is included in the
NEMAX 50 index. Data on institutional ownership are not publicly available

in Germany. Instead, I control for the firm’s free float, which is expected
to be positively associated with turnover. To conduct the test proposed in
section 4, I again include a binary variable representing the firm’s standard
choice (U.S. GAAP = 1). To the extent that U.S. GAAP firms report higher
quality information, the dummy variable is expected to exhibit a positive
coefficient, indicating higher share turnover and hence higher market liq-
uidity for U.S. GAAP firms.
Following the spread model, I use a log-linear specification. The re-
sults, however, are similar using a linear specification or rank regressions. I
also check that multicollinearity among the independent variables is not a
problem.
26
I also estimate rank regressions as a robustness check and find that this specification does
not materially alter my results or conclusions.
TABLE 3
Information Asymmetry–Based Comparison of IAS and U.S. GAAP
2000 With
1999 2000 One-Year Listing
(n = 69) (n = 195) (n = 77)
Panel A: Analysis of bid-ask spreads of IAS versus U.S. GAAP firms
Constant 2.935
∗∗∗
2.123
∗∗∗
2.095
∗∗∗
(8.040) (13.097) (10.143)
U.S. GAAP (−) −0.018 −0.022 −0.001
(−0.402) (−1.013) (−0.033)
Firm size (−) −0.273

∗∗∗
−0.238
∗∗∗
−0.245
∗∗∗
(−12.449) (−16.662) (−14.804)
Share turnover (−) −0.210
∗∗∗
−0.160
∗∗∗
−0.182
∗∗∗
(−3.658) (−9.873) (−6.416)
Volatility (+)0.256
∗∗∗
0.248
∗∗∗
0.265
∗∗∗
(2.879) (6.577) (3.942)
Free float (−) −0.189
∗∗∗
−0.120
∗∗∗
−0.136
∗∗
(−3.078) (−2.451) (−2.308)
Adj. R
2
0.752 0.782 0.817

F -statistic 42.188
∗∗∗
139.851
∗∗∗
68.715
∗∗∗
Panel B: Analysis of turnover of IAS versus U.S. GAAP firms
Constant 1.950
∗∗
2.892
∗∗∗
2.119
∗∗∗
(2.298) (5.894) (2.686)
U.S. GAAP (+)0.007 −0.088 −0.012
(0.069) (−0.972) (−0.087)
Firm size (+/−)0.036 −0.089
∗∗
−0.119
∗∗
(0.700) (−2.375) (−2.009)
Volatility (+)0.572
∗∗
1.289
∗∗∗
1.105
∗∗∗
(2.485) (8.891) (5.361)
Free float (+)0.644
∗∗∗

0.819
∗∗∗
0.560
∗∗∗
(4.512) (6.005) (2.805)
Index inclusion (+)0.278
∗∗
0.183
∗
0.281
(2.191) (1.775) (1.547)
Adj. R
2
0.324 0.394 0.381
F -statistic 7.528
∗∗∗
26.268
∗∗∗
10.369
∗∗∗
The table presents the coefficients and t-statistics from log-linear OLS regressions with White-corrected
standard errors. The regression in the second (third) column is estimated using the sample and data for
1999 (2000) based on all firms listed on the New Market as of April 30, 1999 (April 30, 2000), excluding
those that still follow German GAAP, are traded abroad, and/or are incorporated outside of Germany. The
last column excludes firms that, at the time of variable measurement, are listed on the New Market for
less than one year, traded abroad, and/or incorporated outside of Germany. The dependent variable is the
natural logarithm of the median daily share turnover (i.e., the median daily trading volume divided by the
daily market capitalization). U.S. GAAP is a binary variable indicating the accounting standard choice. Firm
size is the firm’s average market capitalization. Share turnover is the average daily trading volume divided
by the daily market capitalization. Volatility is the standard deviation of daily returns. Free float is equal to 1

minus the percentage of shares closely held. Index inclusion is a binary variable indicating that the firm is
included in the NEMAX 50 index. For further details on the regression variables see table 2. Expected signs
for the variables are in parentheses.
∗
p < .1 (two-sided t-test);
∗∗
p < .05 (two-sided t-test);
∗∗∗
p < .01 (two-sided t-test).
Panel B of table 3 reports the coefficients and t-statistics for OLS regres-
sions with White-corrected standard errors. The R
2
s are comparable to those
reported in prior U.S. studies (e.g., Tkac [1999]). In both years, the U.S.
GAAP dummy is insignificant. In the regression for 2000, the coefficient
is even negative, which may be surprising, but should not be interpreted
460 C. LEUZ
further considering the low t-statistic. The control variables—volatility, free
float, and index inclusion—have the predicted signs and are significant. As
in prior studies, firm size produces mixed results.
27
In summary, there is little evidence that U.S. GAAP firms have a higher
share turnover than do IAS firms. That is, the regressions do not support
the claim that U.S. GAAP are of significantly higher quality than IAS.
5.3 ROBUSTNESS CHECKS
There are three main concerns about the previous findings. The first
concern is correlated omitted variable bias. Note that the ceteris paribus as-
sumption is critical for the link between the quality of accounting standards
and information asymmetry. The second concern is that, even if I have ap-
propriately controlled for all other factors determining information asym-

metry and liquidity, my tests may lack power. The third concern is that firms
choose their reporting strategy, and hence OLS regressions may suffer from
self-selection bias. In the remainder of this article, each of these concerns
is addressed in turn.
5.3.1. Control for Industry Effects. Although I use standard specifications
from the market microstructure literature, the question arises whether the
regressions appropriately control for cross-sectional differences in the firm
characteristics of IAS and U.S. GAAP firms. One way to control for addi-
tional firm characteristics is to control for industry effects because firms in
the same industry are likely to exhibit similar firm characteristics. In addi-
tion, Chordia, Roll, and Subrahmanyam [2000] demonstrate industrywide
liquidity effects. I create seven industry dummies based on the classification
in panel B of table 1. Introducing them into the models does not materially
change the coefficients or the t-statistics of the spread or turnover regres-
sions reported in table 3. Thus, lack of control for industry effects does not
seem to be responsible for the insignificance of the U.S. GAAP variable.
5.3.2. Control for the Length of the Trading History. Another concern is that
many New Market firms have a relatively short trading history. Assuming
frictionless markets, the length of the trading history should have no ef-
fect. In this case, capital markets should immediately reflect existing (and
expected) differences in information asymmetry. In practice, however, it is
conceivable that it takes some time until spreads and turnover reach their
equilibrium levels (e.g., until German investors fully understand IAS and
U.S. GAAP). I address this issue in two ways.
First, I control for the length of the firm’s trading historyin all regressions.
That is, I use the number of trading days from the IPO until April 30, 1999,
27
Estimating the turnover regressions without the firm’s market capitalization as control
variable yields similar results. Similarly, controlling for the bid-ask spread does not alter the
results. Ideally, I would like to estimate spread and turnover regressions simultaneously. The

problem, however, is identifying such a system, as the two variables are proxies for the same
economic construct.
IAS VERSUS US. GAAP 461
and April 30, 2000, respectively, as a control variable. The coefficients and
t-statistics of both spread regressions and the turnover regression for 2000
reported in table 3 are virtually unchanged when this control variable is
introduced. In the turnover regression for 1999, the number of trading
days is significant, indicating higher turnover shortly after the IPO, but the
coefficient for U.S. GAAP (=−0.030) remains insignificant (t =−0.360).
Thus, my conclusions do not change.
Second, I estimate the regressions in 2000 using only firms with a one-year
trading history at the time I start measuring spreads and turnover. After this
restriction, the average sample firm is listed on the New Market for more
than 600 days and has provided between four and five consecutive annual
financial statements to investors (including those in the IPO prospectus).
The results of the restricted sample (also presented in table 3) are similar
to those of the full sample. In both the spread and the turnover regression,
the U.S. GAAP dummy remains insignificant. Thus, the short trading history
of some firms in the full sample does not appear to be responsible for the
insignificance of the U.S. GAAP variable.
5.3.3. Control for Other Disclosures and the Communication with Financial
Analysts. Financial statements are arguably the most important but not the
only way to disclose information to the capital markets. To the extent that
firms compensate deficiencies of the financial statements (or the accounting
standards) with other disclosures, it is important to control for these other
disclosures. For instance, suppose that IAS firms are more forthcoming in
their communication with financial analysts. Then, IAS and U.S. GAAP firms
may exhibit similar levels of information asymmetry and liquidity, even if IAS
is in fact of lower quality than U.S. GAAP.
Before I address this concern, note that there is some evidence that firms

coordinate their disclosures across channels (e.g., Lang and Lundholm
[1996]). This evidence suggests that different disclosures are complements
rather than substitutes. Prior research also documents that different types
of disclosures are associated with firm size (e.g., see Lang and Lundholm
[1993]). Thus, having a proxy for firm size in all my regressions should at
least partially control for other disclosures (including those made to finan-
cial analysts). Both findings mitigate the concern raised earlier.
Nevertheless, I attempt to control explicitly for other disclosures. Based
on Lang and Lundholm [1996], I use the firm’s analyst following as a proxy
for the level of other disclosures and in particular the extent of the firm’s
communication with financial analysts. Including this control variable in the
model produces results that are similar to those reported in table 3. Thus,
even after controlling for other disclosures, there is no evidence that U.S.
GAAP firms exhibit lower information asymmetry or higher liquidity.
5.3.4. Assessment of the Test Power . Although the preceding tests suggest
that my findings are robust, the regressions may lack sufficient statistical
power to detect significant differences between U.S. GAAP and IAS firms.
462 C. LEUZ
One concern is that large standard errors could render the reporting co-
efficient insignificant, even if U.S. GAAP is of higher quality and the effect
of choosing U.S. GAAP on spreads and turnover is large. Another concern
is that power in the New Market setting is low because of the special na-
ture of its firms. I therefore set statistical insignificance aside and gauge the
economic magnitude of the marginal effect of U.S. GAAP reporting.
28
Eval-
uating the estimated reporting coefficient, however, requires a benchmark.
In essence, I need to know how large the reporting coefficient would be if
standard choice mattered and quality differences were substantial. Such a
benchmark is not readily available.

A way to benchmark the estimated reporting coefficients, however, is to
use prior studies documenting that spreads and turnover reflect substantial
differences in firms’ disclosure policies. For instance, Welker [1995] finds
that increasing the firm’s disclosure ratingby one standard deviation reduces
the percentage spread by 20%. Leuz and Verrecchia [2000] estimate that
firms following international instead of German reporting standards exhibit
30% lower (higher) percentage spreads (share turnover).
Compared with these findings, the estimated spread and turnover differ-
ences between IAS and U.S. GAAP firms are small. The spread regressions,
for instance, suggest that the difference between IAS and U.S. GAAP firms is
smaller than 3% of the percentage spread. Thus, provided that the estimated
coefficients are consistent, my findings suggest that the marginal effect of
choosing U.S. GAAP on spreads and turnover is economically small.
29
6. Alternative Proxies for Information Asymmetry
In this section I analyze two alternative proxies for information asymmetry
as an additional robustness check. Prior studies suggest the dispersion of
analysts’ forecasts as a proxy for information asymmetry and the quality
of firms’ disclosures (e.g., Lang and Lundholm [1996], Krishnaswami and
Subramaniam [1998], Clarke and Shastri [2000]).
Based on this idea, I examine whether IAS and U.S. GAAP firms exhibit
significant differences in the dispersion of analysts’ forecasts. I use the dis-
persion of IBES forecasts in the fifth month after the fiscal year-end to en-
sure that the firm’s latest annual financial statements and the first quarterly
report are available at the time of the analysis. Table 2 provides descrip-
tive statistics for forecast dispersion in 1999 and 2000. The sample sizes are
smaller because of missing dispersion data. Although forecast dispersion
28
I also consider the standard error of the reporting coefficient to gauge the statistical power.
I find that I would be able to reject the null hypothesis (at the 5% level) if the marginal effect

of U.S. GAAP reporting were larger than 5% (18%) in the spread (turnover) regression.
29
Consistent with this conclusion and similar to the findings in Leuz and Verrecchia [2000],
an earlier version of this paper reported spread and turnover regressions showing that New
Market firms exhibit roughly 30% lower (higher) spreads (turnover) than MDAX firms using
German GAAP.
IAS VERSUS US. GAAP 463
TABLE 4
Alternative Proxies for Information Asymmetry
Forecast
Dispersion IPO
Panel A: Analysis of in 2000 Panel B: Analysis of Underpricing
Forecast Dispersion (n = 128) IPO Underpricing (n = 188)
Constant 0.048 Constant 0.526
∗∗
(0.391) (2.028)
U.S. GAAP (+/−) −0.033 U.S. GAAP (−) −0.027
(−1.031) (−0.509)
Volatility (+)2.702
∗∗
Offer size (−) −0.095
∗∗
(2.206) (−2.514)
Analyst following (+)0.120
∗∗∗
Free float (+/−) −0.005
∗
(3.838) (−1.755)
Firm size (−) −0.014 Underwriter reputation (+/−)0.003
(−0.920) (1.306)

Index return before IPO (+)0.741
∗∗∗
(7.369)
Industry dummies Included Industry dummies Included
Adj. R
2
0.148 Adj. R
2
0.285
F -statistic 3.003
∗∗∗
F -statistic 7.220
∗∗∗
The table presents coefficients and t-statistics from OLS regressions with White-corrected standard
errors. In panel A, the dependent variable is the dispersion of seven-month analysts’ earnings forecasts
for the fiscal year 2000, measured by the standard deviation of IBES analysts’ forecasts. The regression is
estimated using the sample and data for 2000, excluding 64 firms because of missing data and 3 firms
because of extreme observations. U.S. GAAP is a binary variable indicating the accounting standard choice.
Volatility is the standard deviation of daily returns. Analyst following is the natural logarithm of the number
of analyst forecasts. Firm size is the natural logarithm of the firm’s average market capitalization. For
further details on the regression variables see table 2. In panel B, the dependent variable is the firm’s IPO
underpricing, computed as the return between the first-day closing price and the IPO offer price. The
regression is estimated using the sample for 2000, excluding 7 firms because of missing data. Offer size is
measured as the natural logarithm of the gross IPO proceeds (i.e., the number of shares offered times the
offer price). The free float is the fraction of shares offered at the IPO. Underwriter reputation is measured
by the average rank of the lead (and co-lead) investment bank in terms of its number of New Market lead
bank mandates and total New Market IPO volume. Ranks are assigned such that higher market share results
in higher ranks. The index return before the IPO is measured as the return of the NEMAX All Share index
on the 60 days before the IPO. Industry dummies are based on the classification in panel B of table 1.
Expected signs for the variables are in parentheses.

∗
p < .1 (two-sided t-test);
∗∗
p < .05 (two-sided t-test);
∗∗∗
p < .01 (two-sided t-test).
appears to be smaller for U.S. GAAP firms, the differences in the means and
medians between IAS and U.S. GAAP firms are statistically not significant.
However, these univariate tests do not control for known determinants of
forecast dispersion.
Following Alford and Berger [1999], I control for the firm’s analyst fol-
lowing, share price volatility, and industry effects. In addition, I control for
firm size and include a binary variable for the firm’s standard choice. If
U.S. GAAP and IAS differ in their ability to convey information to financial
analysts, the forecast dispersion for IAS and U.S. GAAP firms is expected to
differ, even though the direction is ambiguous (Basu et al. [2000]).
Because of low data availability, I estimate regressions for 2000 only. Panel
A of table 4 reports these regression results. I find that the differences
in forecast dispersion between IAS and U.S. GAAP firms are statistically
464 C. LEUZ
insignificant after controlling for analyst following, volatility, and firm size.
Thus, the results for forecast dispersion corroborate earlier results for the
spread and turnover.
Another variable commonly associated with information asymmetry is the
level of underpricing at the time of the IPO (e.g., Rock [1986]).
30
Moreover,
Schrand and Verrecchia [2002] provide evidence that firms’ pre-IPO disclo-
sures mitigate underpricing. Based on this notion, I examine whether IAS
and U.S. GAAP firms exhibit significant differences in the extent of IPO

underpricing. If U.S. GAAP is superior in its ability to reduce information
asymmetries or represents a stronger commitment to disclosure, I expect
firms using U.S. GAAP to exhibit lower underpricing than firms employing
IAS.
Univariate tests indicate that the differences in the means (38.2% and
35.6%) and medians (26.4% and 26.5%) for IAS and U.S. GAAP firms,
respectively, are not statistically significant. However, these tests do not con-
trol for known determinants of underpricing. Following the IPO literature, I
control for offer size, the free float at the IPO, the underwriter’s reputation,
and the index return before the IPO. Underpricing generally decreases in
the offer size and increases in pre-IPO index returns (e.g., Beatty and Ritter
[1986]). As Jenkinson and Ljungqvist [2001, p. 72] point out, the predic-
tion for the underwriter’s reputation is not obvious, particularly outside the
United States. Similarly, the predicted sign of the free float at the IPO is
ambiguous and depends on the underpricing theory (e.g., Jenkinson and
Ljungqvist [2001, pp. 79, 129]). In my context, free float likely controls for
rationing and oversubscribed issues. Again, I include industry dummies and
a binary variable for the firm’s standard choice.
Panel B of table 4 reports the regression results for the sample used in
the microstructure tests (except for seven firms with missing data). I find
that the differences in underpricing between IAS and U.S. GAAP firms are
small and statistically insignificant. Thus, the results for IPO underpricing
corroborate earlier results. Similar results are obtained from IPO valuation
regressions (not reported) controlling for sales per share before the IPO,
forecasted sales growth and operating margin, free float, underwriter repu-
tation, and prior index returns. Again, the U.S. GAAP dummy is statistically
insignificant.
31
The findings for the IPO underpricing and valuation regressions also
mitigate the concern that firms’ reporting choices indirectly influence the

market-based control variables in the microstructure tests. The issue is that
market-based control variables (e.g., firm value) could absorb effects that the
reporting dummy is meant to capture, making it harder to find significant
30
The extant literature provides various explanations for underpricing relying on some form
of information asymmetry. For an overview, see Jenkinson and Ljungqvist [2001, pp. 63–107].
31
As robustness check, I drop all accrual-based variables (e.g., operating margin) as they
might be affected by firms’ GAAP choices. The results are not materially altered and the
dummy remains insignificant.
IAS VERSUS US. GAAP 465
differences between IAS and U.S. GAAP firms. But as the IPO underpricing
and valuation regressions do not rely on (firm-specific) market-based con-
trol variables, they are not as prone to this problem and the dummy variable
likely captures all reporting consequences.
32
7. Analysis of Standard Choices in the New Market
In this section I analyze firms’ standard choices for two reasons. First, as
New Market firms choose between the two standards, the previous results may
suffer from selection bias. Thus, I estimate two-stage procedures to check
for selection bias.
Second, firms’ standard choices provide some additional evidence on the
quality of the two standards. The fact that two standards compete in the
New Market suggests that firms trade off the costs and benefits of choosing
IAS and U.S. GAAP.
33
Therefore, firms’ standard choices are likely to reflect
(among other things) the quality and capital market benefits of the two
competing standards. Moreover, the analysis may shed some light on other
factors governing the choice between IAS and U.S. GAAP.

Thus far, the costs and benefits of choosing IAS and U.S. GAAP are not
well understood. There is little empirical research. Peem¨oller, Finsterer, and
Neubert [1999] survey 26 New Market firms about their standard choices.
The responses suggest that competitors’ standard choices and an existing
or intended U.S. listing are key factors in the decision.
According to a more extensive survey conducted by KPMG [2000], CFOs
of large European corporations view implementation costs and access to
capital markets as the key factors influencing standard choice. About two-
thirds of the respondents consider IAS to be cheaper to implement, whereas
they regard U.S. GAAP as preferable in terms of access to capital markets.
KPMG [2000, p. 15], however, points out that the latter position “almost
certainly reflects the SEC’s requirement for foreign companies to present a
reconciliation to U.S. GAAP in order to obtain access to the U.S. markets”
and that it does not necessarily reflect perceptions of the relative quality of
IAS and U.S. GAAP. The survey finds that about 50% of the respondents rate
both standards as being of high quality and close to 50% of the respondents
see no difference between IAS and U.S. GAAP in terms of cost of capital.
It is interesting that the respondents generally view specific accounting dif-
ferences between the two standards as not significant enough to influence
32
To check explicitly for indirect effects on the control variables, I estimate two seemingly
unrelated regressions for IAS and U.S. GAAP firms and conduct Wald tests on the coefficients.
In spread and turnover regressions for 1999 and 2000, I find that the coefficients for IAS
and U.S. GAAP firms are close and that I am unable to reject the null hypothesis for a single
coefficient. These findings suggest that indirect effects on the control variables are likely to be
immaterial in my sample.
33
It is interesting that the split between IAS and U.S. GAAP has been roughly half and half
throughout the history of the New Market.
466 C. LEUZ

standard choice. That is, respondents seem more concerned with the overall
implications of their decision than with specific accounting issues (KPMG
[2000, p. 3]).
The extant empirical literature on voluntary disclosures provides further
guidance regarding the determinants of standard choice. These studies an-
alyze firms’ decisions to provide voluntarily more and higher quality infor-
mation (e.g., Lang and Lundholm [1993]). This literature is relevant in the
context of this study because if U.S. GAAP are in fact of higher quality than
IAS, the determinants identified in these prior studies should also explain
the choice of U.S. GAAP by New Market firms.
34
Based on the extant literature, firm size, current and future financing
needs, and firm performance emerge as the main determinants of corporate
disclosures. The first two are generally positively associated with additional
and higher quality disclosures, whereas the sign of firm performance may
depend on the context and the type of information. In addition, foreign
listings are generally positively associated with corporate disclosures (e.g.,
Saudagaran and Meek [1997]). Thus, provided that U.S. GAAP reporting
provides higher quality disclosures, I hypothesize that the choice of U.S.
GAAP is a function of firm size (+), financing needs (+), and firm perfor-
mance (+/−). I also expect standard choices of competitors to affect firms’
decisions. Recall that all sample firms are listed only in the New Market.
Hence, I do not need to control for foreign listings.
35
I use data from IPO documents because firms are likely to choose their
accounting standard at the same time they decide to list in the New Market.
I measure firm size by total sales in the fiscal year before the IPO. As a proxy
for financing needs, I use the forecasted average sales growth provided at
the time of the IPO. In addition, I control for the firm’s ownership structure
using the free float at the IPO. Firm performance is measured by the firm’s

operating margin in the fiscal year before the IPO. Finally, I control for the
firm’s age and industry membership.
36
Panel A of table 5 reports coefficients and z-statistics for probit regressions.
Firm size and sales growth have the predicted signs. Free float has a negative
coefficient. A possible explanation is that U.S. GAAP firms intend to list in
34
In addition, I rely on prior studies analyzing accounting standard choices in some other
context. For instance, Harris and Muller [1999] examine the decision of non-U.S. firms to
adopt IAS and list in the United States. Leuz and Verrecchia [2000] analyze the decision of
German firms to switch from German GAAP to either IAS or U.S. GAAP. Ashbaugh [2001]
examines the standard choices of non-U.S. firms listed in London and the United States.
35
It is of course conceivable that firms choose U.S. GAAP because they intend to list in the
United States in the future. To the extent that capital markets anticipate future U.S. listing, my
results are biased in favor of U.S. GAAP firms. That is, the absence of a proxy for the propensity
to list in the U.S. makes it easier to reject the null and hence does not explain the insignificance
of the U.S. GAAP variable.
36
In an earlier version, I reported the frequency of Big 5 auditors and included a Big 5
dummy variable in the probit model. However, the fraction of Big 5 auditors is not significantly
different for IAS and U.S. GAAP firms, and the dummy is not significant in the probit model.
IAS VERSUS US. GAAP 467
TABLE 5
Standard Choice and Control for Self-Selection
Panel A: Analysis of standard choice in the New Market
a
1999 (n = 56) 2000 (n = 178)
U.S. GAAP ( = 1) U.S. GAAP ( = 1)
Coefficients z-statistics Coefficients z-statistics

Constant −1.849 −0.957 −0.203 −0.244
Firm size (+) 0.234 0.851 0.094 0.851
Sales growth (+) 3.791
∗∗
2.188 1.144
∗∗∗
2.587
Free float (+) −1.371 −0.928 −0.744
∗
−0.820
Operating margin (+/−) −1.271 −0.789 0.244 1.775
Firm age (+/−) −0.005 −0.188 0.020 1.542
Industry dummies Included Included
McFadden R
2
0.293 0.077
Likelihood ratio statistic 22.574 19.082
Panel B: Spread and turnover regressions controlling for self-selection
b
Bid-Ask Share Turnover
Spread 2000 2000
(n = 178) (n = 178)
Constant 2.050
∗∗∗
Constant 2.702
∗∗∗
(14.268) (4.696)
U.S. GAAP (−)0.010 U.S. GAAP (+) −0.035
(0.133) (−0.106)
Firm size (−) −0.233

∗∗∗
Firm size (+/−) −0.088
∗
(−23.145) (−1.849)
Share turnover (−) −0.160
∗∗∗
Volatility (+)1.242
∗∗∗
(−8.479) (8.113)
Volatility (+)0.237
∗∗∗
Free float (−)0.828
∗∗∗
(5.624) (5.021)
Free float (−) −0.115
∗∗∗
Index inclusion (+)0.180
(−2.835) (1.250)
Inverse Mills ratio −0.018 Inverse Mills ratio −0.026
(−0.381) (−0.123)
Adj. R
2
0.759 0.357
F -statistic 93.773
∗∗∗
17.385
∗∗∗
a
Panel A presents coefficients and z-statistics from probit regressions using the samples for 1999 and
2000, but excluding firms with missing data. The dependent variable is binary indicating the accounting

standard choice (U.S. GAAP = 1). The sample for 1999 (2000) comprises 31 (90) IAS and 25 (88) U.S. GAAP
firms. Financial data are obtained from IPO documents. Firm size is the natural logarithm of total sales in
the fiscal year before the IPO. Sales growth is a proxy for financing needs and measured by the forecasted
average sales growth over the next three years as provided at the time of the IPO. The free float is measured
at the IPO. The firm’s operating margin is operating income (EBIT) divided by total sales and measured in
the fiscal year before the IPO. Firm age is the number of years since the incorporation. Industry dummies
are based on the classification in panel B of table 1. Expected signs for the variables are in parentheses.
b
Panel B is based on the two-stage model outlined in section 6. It presents the coefficients and z-statistics
from the second stage. Standard errors are adjusted following Maddala [1983]. The dependent variable
is in the second (last) column is the percentage spread (percentage turnover). The specification is log
linear as in table 3. U.S. GAAP is a binary variable indicating the accounting standard choice. Firm size is
the average market capitalization. Share turnover is the average daily trading volume divided by the daily
market capitalization. Volatility is the standard deviation of daily returns. Free float is equal to 1 minus the
percentage of shares closely held. Index inclusion is a binary variable indicating that the firm is included in
the NEMAX 50 index. The inverse Mills ratio is computed from the probit model in panel A. For further
details on the regression variables, see table 2. Expected signs for the variables are in parentheses.
∗
p < .1 (two-sided t-test);
∗∗
p < .05 (two-sided t-test);
∗∗∗
p < .01 (two-sided t-test).
468 C. LEUZ
the United States in the future and therefore retain a larger fraction of the
firm. This intention may offset the positive effect of free float on disclosures.
Sales growth is the only variable that is significant in both years. This finding
is consistent with the perception that U.S. GAAP is preferable for firms with
large future financing needs because it allows them to tap into the U.S.
capital markets (KPMG [2000]). As mentioned before, this finding may be

areflection of the SEC requirements and not necessarily of the standard
quality. Firm performance is significant at the 10% level in 2000. Two (one)
industry dummies are significant at the 10% level in 2000 (1999).
Although the low significance levels of most variables may be disappoint-
ing, they are consistent with my other findings. Recall that the variables
are chosen based on the hypothesis that the choice of U.S. GAAP leads to
higher quality disclosures. If, however, the two standards are either compa-
rable or do not affect disclosure quality, as my earlier results suggest, I would
not expect such variables to have high explanatory power. Furthermore, the
results are consistent with the KPMG [2000] survey.
Finally, I check whether previous results are affected by selection bias.
To take into account the fact that firms can choose between IAS and U.S.
GAAP, I estimate a two-stage treatment effects model (see Barnow, Cain, and
Goldberger [1980], Maddala [1983]). The role of the first stage is to con-
trol for self-selection. The second stage estimates the association between the
spread (turnover) and the firm’s reporting choice as well as other firm char-
acteristics taking into account that the reporting variable is endogenous. To
implement this model, I estimate inverse Mills ratios with the probit regres-
sions and include them in the spread and turnover regressions to account
for self-selection (e.g., Barnow, Cain, and Goldberger [1980]).
In both years the estimated coefficients of the inverse Mills ratio are in-
significant in my spread and turnover regressions. The p-values range be-
tween 0.403 and 0.902. Panel B of table 5 presents the results for the spread
and turnover based on the sample for 2000. The results for 1999 are qualita-
tively similar. Overall, the coefficients and significance levels of the variables
are not materially different from those reported in table 3. In particular, the
U.S. GAAP coefficient remains insignificant in all regressions. Thus, selec-
tion bias does not appear to be a severe problem. This conclusion obviously
hinges on the ability of the probit model to control for self-selection and
our understanding of firms’ standard choices.

8. Conclusions
This study is motivated by the global accounting debate about IAS and
U.S. GAAP. The debate focuses primarily on comparisons of the stipulated
accounting methods per se. There is, however, little empirical evidence on
the standards’ economic consequences in capital markets. This study con-
tributes a market-based test to this debate. I investigate whether firms using
U.S. GAAP vis-`a-vis IAS exhibit differences in several proxies for informa-
tion asymmetry. The study exploits the requirement that firms trading in
IAS VERSUS US. GAAP 469
Germany’s New Market must choose between IAS and U.S. GAAP for finan-
cial reporting purposes but are subject to the same regulatory environment
otherwise. Thus, other institutional factors such as listing requirements and
enforcement of accounting standards are held constant.
In this setting I find that the differences in the bid-ask spreads and share
turnover between IAS and U.S. GAAP firms are economically and statistically
insignificant. Several robustness checks and subsequent analyses of analyst
forecast dispersion, IPO underpricing, IPO valuation, and firms’ standard
choices provide corroborating evidence. Thus, at least in the New Market,
IAS and U.S. GAAP firms do not exhibit significant differences in several
information asymmetry proxies. These findings do not support claims that
U.S. GAAP produce financial statements of higher informational quality
than do IAS.
The results are consistent with at least two interpretations. Based on the
view that accounting standards have major consequences in capital markets,
the results suggest that IAS and U.S. GAAP are comparable in reducing
information asymmetries. However, the findings are also consistent with the
interpretation that, despite differences in the standards, New Market firms
exhibit similar accounting quality precisely because firms face similar market
forces and institutional factors, resulting in similar reporting incentives. This
view relies on recent findings that accounting quality is largely determined

by market forces and institutional factors, rather than accounting standards
(e.g., Ball, Robin, and Wu [Forthcoming]) The explanation is that firms
can exceed and to some extent circumvent mandated reporting standards,
thereby reducing their influence on observed accounting and disclosure
quality.
Finally, although confining attention to New Market firms offers several
advantages in research design, the setting also has limitations. The results
should therefore be interpreted cautiously bearing in mind that the sample
choice could reduce test power, the results need not extend to other firms
and settings, and that the study does not directly address policy questions
faced by national standard setters.
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