ias versus u.s. gaap: information asymmetry–based … · capital markets (see also pownall ......

Journal of Accounting ResearchVol. 41 No. 3 June 2003

Printed in U.S.A.

IAS Versus U.S. GAAP:Information Asymmetry–Based

Evidence from Germany’sNew Market

C H R I S T I A N L E U Z ∗

Received 3 October 2001; accepted 7 November 2002

ABSTRACT

Motivated by the debate about globally uniform accounting standards, thisstudy investigates whether firms using U.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 uniquesetting in which the two sets of standards are put on a level playing field. Firmstrading in Germany’s New Market must choose between IAS and U.S. GAAPfor 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, differencesin the bid-ask spread and share turnover between IAS and U.S. GAAP firmsare 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, ChristianLaux, S. P. Kothari, Claudia Roder, 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. GoetheUniversitat Frankfurt, MIT, University of Michigan, Stanford University, Tilburg University, theEAA Meetings (Munich) and the EFA Meetings (Barcelona). I would also like to thank UweSchweickert (Deutsche Borse), Peter Gomber (Deutsche Borse), Jorg Hueber (KPMG), RainerJager (PWC), and IBES for generously providing data for this study, and Tobias Herwig for hisexcellent research assistance. I also gratefully acknowledge financial support by the WhartonElectronic Business Initiative (WeBI).

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Copyright C©, University of Chicago on behalf of the Institute of Professional Accounting, 2003

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analysts’ forecast dispersion, initial public offering underpricing, and firms’standard choices corroborate these findings. Thus, at least for New Marketfirms, the choice between IAS and U.S. GAAP appears to be of little conse-quence for information asymmetry and market liquidity. These findings donot support widespread claims that U.S. GAAP produce financial statementsof higher informational quality than IAS.

1. Introduction

This study is motivated by the debate about the two leading contenders inthe global competition among financial reporting regimes: U.S. generallyaccepted accounting principles (GAAP) and international accounting stan-dards (IAS). This debate, which is summarized in section 2, focuses primarilyon comparisons of the stipulated accounting methods per se. There is, how-ever, little empirical evidence on the standards’ economic consequences incapital markets (see also Pownall and Schipper [1999]).

In this article I investigate whether firms using U.S. GAAP vis-a-vis IASexhibit cross-sectional differences in several proxies for information asym-metry, such as bid-ask spreads and share turnover. I focus on these proxiesbecause reducing information asymmetries and increasing market liquidityis one, albeit an important, concern in securities and accounting regulation(e.g., Loss and Seligman [2001]). Moreover, in using these proxies, the testsare not restricted to comparisons of summary accounting measures such asearnings but capture differences in financial reporting information morebroadly (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 NewMarket are required to choose between IAS and U.S. GAAP for financialreporting 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 heldconstant. 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 basisof 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 shareturnover across IAS and U.S. GAAP firms are statistically insignificant andeconomically small. For instance, the spread regressions suggest that, set-ting statistical significance aside, the effect of U.S. GAAP reporting is lessthan 3% of the percentage spread. Next, I examine analysts’ forecast disper-sion and initial public offering (IPO) underpricing as alternative proxiesfor information asymmetry and find that the differences are also statisti-cally insignificant. Finally, I analyze firms’ standard choices and check forselection bias with two-stage regressions. These tests corroborate the otherfindings. In summary, the choice of IAS or U.S. GAAP appears to be of littleconsequence 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 setsof standards, at least in terms of their ability to reduce information asym-metries. The evidence does not support claims that U.S. GAAP producefinancial 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 marketforces 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 andShivakumar [2002]). Together, the studies provide evidence suggesting thatthe global accounting debate focuses too much on the standards choice andtoo little on market forces and institutional factors, as also argued by Ball[2001].

Although the New Market setting offers several advantages, there arecaveats that should be borne in mind when interpreting the results. First,New Market firms are young growth firms that are strongly dependent onequity financing. Although information asymmetry and disclosure issues arepertinent for such firms (Smith and Watts [1992]), financial statements (ofany kind) may not be as important or serve special purposes, reducing thepower of my tests. Moreover, it is unclear whether the findings generalize tofirms 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 termsof 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 thisstudy. Third, New Market firms choose their accounting standards. Thus,my results are only valid to the extent that I have appropriately controlledfor selection bias. Finally, the paper does not address the policy question ofwhether a country should accept or switch to IAS.1

The remainder of the paper is organized as follows. Section 2 sketchesthe 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 shareturnover. 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] cautionabout drawing policy implications from market-based tests.

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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) wasfounded in 1973 to set international accounting standards and promotetheir global acceptance. In response to criticism of its early standards, theIASC embarked on the Comparability/Improvements Project in 1987. Therevised standards, which became effective in 1995, substantially reducedthe number of accounting choices. In July 1995, the IASC and InternationalOrganization of Securities Commissions (IOSCO) agreed on a list of ac-counting issues that needed to be addressed by any set of standards seekingIOSCO’s endorsement for cross-border offerings and listings. The ensuingCore Standards Project led to substantial revisions of IAS. By March 1999,the IASC completed all but one of those issues and subsequently receivedIOSCO’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 tobecome the global set of accounting standards have led to a debate abouttheir relative quality. Since then, several security regulators such as the U.S.Securities and Exchange Commission (SEC) and the Canadian SecuritiesAdministrators (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 improvedsubstantially 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’ equityfor eight companies under both standards. He concludes that firms com-plying with revised IAS provide accounting measures that are essentiallyconsistent 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 thatdisclosures are sufficient to allow investors to make their own inferences inthose instances where substantial differences remain or IAS permit severalaccounting 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 thatCFOs of large European corporations view IAS as offering similar qualitywhile 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 ofForeign Companies,” Wall Street Journal , February 18, 2000, p. A3.


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 TheFinancial Accounting Standards Board (FASB [1999]), for instance, pointsto more than 250 key differences in four categories: recognition, measure-ment, permissible alternatives, and lack of requirements or guidance.4 Basedon this comparison, the FASB concludes that IAS are of lower quality thanU.S. GAAP.5

In summary, there are opposing views on the quality of IAS relative toU.S. GAAP, but the debate focuses on the stipulated accounting methodsthemselves rather than any empirical evidence. Prior studies focus largely oncomparing foreign and U.S. GAAP financial statements, for instance, withrespect 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] compareGerman firms following U.S. GAAP or IAS with firms following GermanGAAP.

A few studies explicitly address the relative quality of IAS and U.S. GAAPand 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 reconciliationmagnitudes, IAS are closer to U.S. GAAP than other foreign GAAP but thatreconciliation items are incrementally value relevant.6 They interpret theirfindings as evidence that IAS and U.S. GAAP accounting measures are notsubstitutes. However, as Pownall and Schipper [1999] point out, evidencefrom 20-F reconciliations is unlikely to be representative of IAS (or foreignGAAP) 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 andU.S. GAAP earnings and book values of equity are equally value relevantbut 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 StreetJournal , 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 updatedcomparisons.

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 significantlyrelated 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.

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a small sample of firms, most of which are also traded in the United Statesand hence do not control for potentially confounding listing, enforcement,or other institutional effects. Moreover, the tests focus solely on summaryaccounting measures and hence do not account for footnote disclosuresthat may compensate for recognition differences.

Finally, several recent studies find that accounting quality is determinedprimarily by market forces and institutional factors, rather than account-ing standards (e.g., Ball, Robin, and Wu [Forthcoming], Leuz, Nanda, andWysocki [Forthcoming]). These findings suggest that standards per se donot 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 empiricalquestion.

3. The New Market in Germany

The New Market (or Neue Markt) was launched in March 1997 as a newGerman stock market segment geared toward small- and medium-size com-panies in innovative and fast-growing industries. Within a few months ofits inception, it became Europe’s most successful equity market for growthfirms, 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 Borse decided to reorganize its markets and stop singling outgrowth and technology stocks in a segment. In 2003, New Market firms arebeing reassigned to two newly created market segments, called Prime andGeneral Standard. The Prime Standard segment inherits the strict listingand disclosure requirements of the New Market, which go substantially be-yond those of the General Standard.9 In addition, new securities regulationis under way to address enforcement problems that have become apparentduring 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 vielfaltig geschutzt,”Frankfurter Allgemeine Zeitung , Septermber 5, 2001, p. 208; “Neuer Markt,” Frankfurter AllgemeineZeitung (Supplement), March 6, 2001.

9 See “Neuer Markt Closure, Comment & Analysis,” Financial Times, September 27, 2002,p. 11.

10 The Deutsche Borse tightened the rules several times to address problems as they becameapparent. For instance, in March 2001, it introduced rules that (1) require disclosure of allshare transactions by managers, board members, and the company itself; (2) standardize andextend quarterly financial reports; and (3) increase penalties for rule violations, including finesup to 100,000 EUR and delisting. See A. Kueppers, “Following in the Shadow of Nasdaq, NeuerMarkt 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.


The New Market’s rules were deliberately chosen to exceed traditionalGerman listing and disclosure requirements because New Market firms arecharacterized by substantial uncertainty about business prospects and man-agement expertise.11 To describe briefly the key rules, the New Market’sRegelwerk 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 Thereare extensive and detailed disclosure requirements for the IPO prospectus(Regelwerk, §4). In particular, firms have to provide comparable financialstatements for three previous fiscal years. Subsequently, firms have to pre-pare and publish annual financial statements no later than three monthsafter the fiscal year end (Regelwerk, §7). Financial statements have to be inaccordance with either IAS or U.S. GAAP. In addition, firms must publishquarterly reports within two months after each quarter and hold at least oneanalyst 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, auditorsand directors could face criminal prosecution for misleading or fraudulentfinancial statements (§§331 and 332 HGB). It is also possible to sue fordamages in civil courts, but only after a conviction in criminal proceedings.However, as U.S.-style shareholder litigation or SEC-like monitoring does notexist in Germany, enforcement is unlikely to be as strong as in the UnitedStates. For this reason, I exclude New Market firms with U.S. listings fromthe sample. The concern is that differential enforcement could otherwisebias the tests. However, I note that weak enforcement likely reduces thepower of my tests.

Mitigating this concern, Glaum and Street [Forthcoming] find that thecompliance of New Market firms with required disclosures is on averagereasonably high.13 They also show that firms with U.S. listings exhibit highercompliance levels than do firms without such listings. However, once thiseffect is controlled for, the compliance levels of IAS firms are only slightlylower (≈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. GAAPfirms.

Finally, as my empirical tests are based on bid-ask spreads and shareturnover, 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 fur hohe Transparenz amNeuen Markt,” Frankfurter Allgemeine Zeitung , September 25, 2000, p. 32.

12 The Regelwerk is available online at http://deutsche-boerse.com/nm/.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 complianceof IAS and U.S. GAAP firms with the New Market’s quarterly reporting rules.

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Shares are traded simultaneously on the floor and on an electronic tradingplatform (Xetra). Floor trading is organized as an auction system only. Theelectronic trading system, which is a hybrid between an auction and market-maker system, allows traders to post limit orders. Spreads arise from the bestbid 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 providebinding bid and ask limit orders (or quotes) for the three daily auctions andupon request by a market participant (with a maximum response time of120 seconds).15 The sponsors’ minimum quote volume is 20,000 EUR andtheir quoted spreads must not exceed 4%. The exchange monitors spon-sor performance (since October 1999) and publish ratings (since January2000). 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., Copelandand Galai [1983], Glosten and Milgrom [1985]). Information asymmetriesare costly to firms, as investors adjust prices to compensate for holdingshares in illiquid markets. Increasing the level or precision of disclosureshould reduce the likelihood of information asymmetries between investorsand 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 differencebetween 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 andVerrecchia [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 investorsand 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 greaterinvestor confidence, which improves liquidity, [and] reduces capital costs”(see also FASB [1999, p. 3]).

The preceding discussion suggests information asymmetry–based tests as away to assess the economic substance of the global accounting debate and, inparticular, the arguments put forth in favor of U.S. GAAP. The tests examinewhether, ceteris paribus, firms employing U.S. GAAP exhibit less information

15 For details, see Designated Sponsor Guide, http://deutsche-boerse.com/nm/.


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, theneither IAS and U.S. GAAP are comparable in reducing information asym-metries, consistent with the argument of IAS proponents, or standards donot 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 donot have immediate tax or dividend implications. In Germany, taxation andlegal dividend restrictions are not based on consolidated (or group) finan-cial statements. Under the Commercial Code, such statements serve purelyinformational purposes.

I analyze whether IAS and U.S. GAAP firms in the New Market exhibitcross-sectional differences in the bid-ask spread and share turnover, both ofwhich are standard proxies for information asymmetry and market liquidity.Although spread data are not readily available for the New Market, theDeutsche Borse 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 measuredafter the New Market All Share index had gained 24% from January to theend of May. In 2000, it had lost almost 35% from its peak in March to thebeginning of the measurement interval. Analyzing both periods serves asa robustness check that the results are not specific to the New Market’sboom phase. However, sharp market movements, such as those of the NewMarket in 1999 and 2000, could also make the proxies more cross-correlatedand less powerful for my purposes because investors are more likely to relyon marketwide information rather than firm-specific information in thesetimes.17 It is therefore noteworthy that the measurement intervals themselvesare comparatively stable periods, where the New Market All Share indexposted 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 intocomponents related and unrelated to information asymmetry. There are,however, several institutional features that mitigate this data limitation andmake 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 thereforeexplicitly addressed in the robustness checks and should be kept in mind as a caveat wheninterpreting 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 than3,000 individual spreads.

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information asymmetry.19 First, spreads arise from limit orders posted in theelectronic trading system by all traders, instead of the quotes of a specialist ora few market makers. In such a market, other spread components unrelatedto information asymmetry, such as inventory-holding costs or monopolyrents, should be smaller. Empirical comparisons of order- and quote-drivenmarkets support this conjecture (e.g., Huang and Stoll [1996]). Second,traders are charged for order processing separately, and New Market firmspay fees to their designated sponsors to compensate them for their service.For these reasons, order-processing costs are unlikely to be a major spreadcomponent. Third, trades are executed automatically, which implies that thequoted spreads are the effective spreads. Finally, share prices are quoted withtwo decimal places, which reduces price discreteness and should increasethe 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 factorsunrelated to information asymmetry, such as portfolio rebalancing, liquidityshocks, 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 Asymmetryand Market Liquidity

5.1 SAMPLE SELECTION AND DESCRIPTIVE STATISTICS

As of April 30, 1999, 90 firms were listed in the New Market. I eliminatefirms that are incorporated outside of Germany (6), listed abroad (5), orboth (5). This restriction reduces the sample to 74 firms but ensures thatall 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 intheir annual reports.21 Thus, the final sample for 1999 contains 69 firms. Toincrease the sample, I also perform my analyses using the 246 firms listedin 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 ofspreads. Thus, it is not obvious whether the decomposition increases or decreases measurementerror.

20 Some New Market firms are also listed on the Geregelten Markt of regional exchangesor traded in the Freiverkehr (OTC market). However, the disclosure and listing requirementfor these market segments are limited compared with the New Market. Moreover, a listing onthe New Market entails a private contract with the Deutsche Borse and a registration for theGeregelten Markt in Frankfurt.

21 In its early days, the New Market allowed some firms to provide German GAAP financialstatements for a limited time if they were temporarily unable to prepare them according toIAS or U.S. GAAP. By April 30, 2000, all firms follow either IAS or U.S. GAAP in their annualreports.


T A B L E 1Descriptive Statistics on Accounting Standard Choices

Panel A: Accounting standard choices in the New Marketa

All Firms Listed as Sample for 1999 All Firms Listed as Sample for 2000of April 30, 1999 (n = 69 firms) of April 30, 2000 (n = 195 firms)

IAS 42 40 117 102US GAAP 43 29 129 93

Panel B: Distribution of accounting standards by industryb

Sample for 1999 Sample for 2000

IAS U.S. GAAP IAS U.S. GAAP

Bio- and Med-Technology 1 1 6 7Industrials & Industrial Services 4 3 6 3Internet 3 6 15 28IT Services 1 4 14 12Media & Entertainment 7 2 17 9Software 10 3 18 12Technology 10 8 20 16Telecommunications 4 2 6 6

aAs of April 30, 1999, 90 firms were listed in the New Market. Five of them follow German GAAP fortheir 1998 annual report and hence are excluded (see footnote 21). Thus, the first column comprises 85firms. The sample for 1999 (second column) excludes firms that are incorporated outside Germany and/orare listed on a foreign exchange. The third column comprises all 246 firms listed in the New Market as ofApril 30, 2000. The sample for 2000 (last column) excludes firms that are incorporated outside Germanyand/or are listed on a foreign exchange.

bPanel B is based on the industry classification provided for the New Market by the Deutsche Borse(http://www.neuer-markt.de).

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 firmsand all New Market firms as of April 30, 1999, and April 30, 2000. The panelshows that IAS and U.S. GAAP are fairly evenly distributed across firms. Thepercentage of U.S. GAAP firms is smaller in my samples than in the entiremarket because firms that are eliminated because of their foreign listingoften trade in the U.S. and use U.S. GAAP. Panel B reports firms’ standardchoices by industry. Both standards are fairly evenly distributed within mostindustries, except in Media & Entertainment and in Internet industries,where firms seem to prefer IAS and U.S. GAAP, respectively. Subsequenttests therefore check for industry effects.

Table 2 provides descriptive statistics for the dependent variables and firmcharacteristics by accounting standard choice. The table reports the averagepercentage spread from June 1, 1999, to July 31, 1999, from June 1, 2000,to August 31, 2000, respectively, and the median daily share turnover fromMay 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 conceptuallya 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.

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T A B L E 2Descriptive 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 1.751spread 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 0.071turnover 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 0.039volatility 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 0.296ALL 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 3.000following 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 0.170dispersion 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, andApril 30, 2000, respectively, excluding those that still follow German GAAP, are incorporated outside ofGermany, and/or are listed on a foreign exchange (see table 1 for details). Spread data have been providedby Deutsche Borse. The spread is expressed as a percentage and computed as the difference between thebest bid and ask divided by the midpoint. For each stock, the exchange provides a monthly average of allspreads that existed in the electronic XETRA trading system (see discussion in section 4). The table reportsthe 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 isexpressed as a percentage and computed for 60 trading days as the median of daily volume in Euro dividedby daily market capitalization in Euro from May 1, 1999, to July 31, 1999, and from June 1, 2000, to August31, 2000, respectively. The market capitalization (in millions of Euro) is measured as the average marketvalue 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 Borse Online (based on ownershipdata 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) wasobtained from IBES. Forecast dispersion is the standard deviation of the seven-month consensus forecastfor the fiscal years 1999 and 2000. Asterisks indicate that the means (medians) of IAS and U.S. GAAP firmsare 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 particularevent. Using the average turnover, however, produces similar results.

The descriptive statistics show that the New Market’s average spread andaverage share turnover are considerably lower in 2000 than in 1999. Thesharp decline in share turnover likely reflects the end of the new economy


boom and the market downturn. Continuous efforts of Deutsche Borse toimprove market structure and trading efficiency could explain the reductionin spreads. For instance, as described in section 3, the Deutsche Borse startedmonitoring sponsor performance in October 1999 and publishing sponsorratings in January 2000, which could have reduced the average spread inthe market. As marketwide fluctuations in liquidity and microstructure im-provements apply to all firms, they are unlikely to affect my cross-sectionaltests.23

The differences in the spread and share turnover across U.S. GAAP andIAS firms are small and statistically insignificant for both the groups’ meansand medians. But as these univariate comparisons do not control for spreadand turnover determinants, they should be interpreted cautiously. Table 2also presents descriptive statistics for other firm characteristics, showing thatthe 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 spreadand share turnover between IAS and U.S. GAAP firms controlling for firmcharacteristics. I report the results for 1999 and 2000 using the samplesdescribed in the previous section.

5.2.1. Bid-Ask Spreads. The bid-ask spread model is based on the extantliterature. Prior studies suggest that the percentage spread is negatively asso-ciated with trading volume, firm size, and market-maker competition, andpositively 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 respectiveintervals 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 mixedsignals about changes in (aggregate) liquidity. Although both proxies are related to the sameeconomic 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 isconceivable that changes in these other factors are responsible for the joint decrease in spreadsand turnover (see also Chordia, Roll, and Subrahmanyam [2001]).

24 See table 2 for details. Turnover is used as opposed to unscaled trading volume to avoidmulticollinearity problems with market capitalization.

25 In an earlier version, I reported spread regressions including the number of designatedsponsors as a control variable. These regressions are close to those in table 3 and yield aninsignificant 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 onlythe from market-maker quotes (see also the discussion in section 4). Similarly, controlling forsponsor ratings does not materially affect results.

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I introduce a binary variable into the model indicating the firm’s reportingchoice (U.S. GAAP = 1). To the extent that U.S. GAAP firms report higherquality information, the dummy variable is expected to exhibit a negative co-efficient indicating lower spreads and hence lower information asymmetryfor U.S. GAAP firms.

As most analytical models identify multiplicative relations between thespread 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 basedon Belsley, Kuh, and Welsch [1980] suggest that multicollinearity amongthe independent variables is not a problem.

Panel A of table 3 presents the coefficients and t-statistics for ordinaryleast squares (OLS) regressions with White-corrected standard errors. Theregressions 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. GAAPdummy is negative, but not statistically significant. All other variables havethe expected signs and are highly significant.

In summary, there is little evidence that firms employing U.S. GAAP havelower bid-ask spreads than firms using IAS. Thus, the regressions do notsupport the claim that U.S. GAAP are of significantly higher quality thanIAS.

5.2.2. Share Turnover . The turnover model is also based on the extantliterature. Prior studies suggest that share turnover is related to firm size andpositively associated with volatility, institutional ownership, and the inclusionin 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 and2000, and a binary variable indicating whether the firm is included in theNEMAX 50 index. Data on institutional ownership are not publicly availablein Germany. Instead, I control for the firm’s free float, which is expectedto be positively associated with turnover. To conduct the test proposed insection 4, I again include a binary variable representing the firm’s standardchoice (U.S. GAAP = 1). To the extent that U.S. GAAP firms report higherquality information, the dummy variable is expected to exhibit a positivecoefficient, 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. Ialso check that multicollinearity among the independent variables is not aproblem.

26 I also estimate rank regressions as a robustness check and find that this specification doesnot materially alter my results or conclusions.

T A B L E 3Information Asymmetry–Based Comparison of IAS and U.S. GAAP

2000 With1999 2000 One-Year Listing

(n = 69) (n = 195) (n = 77)

Panel A: Analysis of bid-ask spreads of IAS versus U.S. GAAP firmsConstant 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. R2 0.752 0.782 0.817F -statistic 42.188∗∗∗ 139.851∗∗∗ 68.715∗∗∗

Panel B: Analysis of turnover of IAS versus U.S. GAAP firmsConstant 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. R2 0.324 0.394 0.381F -statistic 7.528∗∗∗ 26.268∗∗∗ 10.369∗∗∗

The table presents the coefficients and t-statistics from log-linear OLS regressions with White-correctedstandard errors. The regression in the second (third) column is estimated using the sample and data for1999 (2000) based on all firms listed on the New Market as of April 30, 1999 (April 30, 2000), excludingthose that still follow German GAAP, are traded abroad, and/or are incorporated outside of Germany. Thelast column excludes firms that, at the time of variable measurement, are listed on the New Market forless than one year, traded abroad, and/or incorporated outside of Germany. The dependent variable is thenatural logarithm of the median daily share turnover (i.e., the median daily trading volume divided by thedaily market capitalization). U.S. GAAP is a binary variable indicating the accounting standard choice. Firmsize is the firm’s average market capitalization. Share turnover is the average daily trading volume dividedby the daily market capitalization. Volatility is the standard deviation of daily returns. Free float is equal to 1minus the percentage of shares closely held. Index inclusion is a binary variable indicating that the firm isincluded in the NEMAX 50 index. For further details on the regression variables see table 2. Expected signsfor 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 R2s are comparable to thosereported 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 coefficientis even negative, which may be surprising, but should not be interpreted

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further considering the low t-statistic. The control variables—volatility, freefloat, and index inclusion—have the predicted signs and are significant. Asin prior studies, firm size produces mixed results.27

In summary, there is little evidence that U.S. GAAP firms have a highershare turnover than do IAS firms. That is, the regressions do not supportthe 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 firstconcern is correlated omitted variable bias. Note that the ceteris paribus as-sumption is critical for the link between the quality of accounting standardsand 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 firmschoose their reporting strategy, and hence OLS regressions may suffer fromself-selection bias. In the remainder of this article, each of these concernsis addressed in turn.

5.3.1. Control for Industry Effects. Although I use standard specificationsfrom the market microstructure literature, the question arises whether theregressions appropriately control for cross-sectional differences in the firmcharacteristics of IAS and U.S. GAAP firms. One way to control for addi-tional firm characteristics is to control for industry effects because firms inthe same industry are likely to exhibit similar firm characteristics. In addi-tion, Chordia, Roll, and Subrahmanyam [2000] demonstrate industrywideliquidity effects. I create seven industry dummies based on the classificationin panel B of table 1. Introducing them into the models does not materiallychange 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 notseem 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 thatmany New Market firms have a relatively short trading history. Assumingfrictionless markets, the length of the trading history should have no ef-fect. In this case, capital markets should immediately reflect existing (andexpected) differences in information asymmetry. In practice, however, it isconceivable that it takes some time until spreads and turnover reach theirequilibrium levels (e.g., until German investors fully understand IAS andU.S. GAAP). I address this issue in two ways.

First, I control for the length of the firm’s trading history in 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 controlvariable yields similar results. Similarly, controlling for the bid-ask spread does not alter theresults. Ideally, I would like to estimate spread and turnover regressions simultaneously. Theproblem, however, is identifying such a system, as the two variables are proxies for the sameeconomic construct.


and April 30, 2000, respectively, as a control variable. The coefficients andt-statistics of both spread regressions and the turnover regression for 2000reported in table 3 are virtually unchanged when this control variable isintroduced. In the turnover regression for 1999, the number of tradingdays is significant, indicating higher turnover shortly after the IPO, but thecoefficient 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-yeartrading history at the time I start measuring spreads and turnover. After thisrestriction, the average sample firm is listed on the New Market for morethan 600 days and has provided between four and five consecutive annualfinancial statements to investors (including those in the IPO prospectus).The results of the restricted sample (also presented in table 3) are similarto those of the full sample. In both the spread and the turnover regression,the U.S. GAAP dummy remains insignificant. Thus, the short trading historyof some firms in the full sample does not appear to be responsible for theinsignificance of the U.S. GAAP variable.

5.3.3. Control for Other Disclosures and the Communication with FinancialAnalysts. Financial statements are arguably the most important but not theonly way to disclose information to the capital markets. To the extent thatfirms compensate deficiencies of the financial statements (or the accountingstandards) with other disclosures, it is important to control for these otherdisclosures. For instance, suppose that IAS firms are more forthcoming intheir communication with financial analysts. Then, IAS and U.S. GAAP firmsmay exhibit similar levels of information asymmetry and liquidity, even if IASis in fact of lower quality than U.S. GAAP.

Before I address this concern, note that there is some evidence that firmscoordinate their disclosures across channels (e.g., Lang and Lundholm[1996]). This evidence suggests that different disclosures are complementsrather than substitutes. Prior research also documents that different typesof 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 atleast 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. Basedon Lang and Lundholm [1996], I use the firm’s analyst following as a proxyfor the level of other disclosures and in particular the extent of the firm’scommunication with financial analysts. Including this control variable in themodel 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 suggestthat my findings are robust, the regressions may lack sufficient statisticalpower to detect significant differences between U.S. GAAP and IAS firms.

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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 effectof choosing U.S. GAAP on spreads and turnover is large. Another concernis 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 theeconomic 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 ifstandard choice mattered and quality differences were substantial. Such abenchmark is not readily available.

A way to benchmark the estimated reporting coefficients, however, is touse prior studies documenting that spreads and turnover reflect substantialdifferences in firms’ disclosure policies. For instance, Welker [1995] findsthat increasing the firm’s disclosure rating by one standard deviation reducesthe percentage spread by 20%. Leuz and Verrecchia [2000] estimate thatfirms following international instead of German reporting standards exhibit30% 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 issmaller than 3% of the percentage spread. Thus, provided that the estimatedcoefficients are consistent, my findings suggest that the marginal effect ofchoosing 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 asymmetryas an additional robustness check. Prior studies suggest the dispersion ofanalysts’ forecasts as a proxy for information asymmetry and the qualityof firms’ disclosures (e.g., Lang and Lundholm [1996], Krishnaswami andSubramaniam [1998], Clarke and Shastri [2000]).

Based on this idea, I examine whether IAS and U.S. GAAP firms exhibitsignificant 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 quarterlyreport are available at the time of the analysis. Table 2 provides descrip-tive statistics for forecast dispersion in 1999 and 2000. The sample sizes aresmaller 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 effectof 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 NewMarket firms exhibit roughly 30% lower (higher) spreads (turnover) than MDAX firms usingGerman GAAP.


T A B L E 4Alternative Proxies for Information Asymmetry

ForecastDispersion IPO

Panel A: Analysis of in 2000 Panel B: Analysis of UnderpricingForecast 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. R2 0.148 Adj. R2 0.285F -statistic 3.003∗∗∗ F -statistic 7.220∗∗∗

The table presents coefficients and t-statistics from OLS regressions with White-corrected standarderrors. In panel A, the dependent variable is the dispersion of seven-month analysts’ earnings forecastsfor the fiscal year 2000, measured by the standard deviation of IBES analysts’ forecasts. The regression isestimated using the sample and data for 2000, excluding 64 firms because of missing data and 3 firmsbecause 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 numberof analyst forecasts. Firm size is the natural logarithm of the firm’s average market capitalization. Forfurther details on the regression variables see table 2. In panel B, the dependent variable is the firm’s IPOunderpricing, computed as the return between the first-day closing price and the IPO offer price. Theregression is estimated using the sample for 2000, excluding 7 firms because of missing data. Offer size ismeasured as the natural logarithm of the gross IPO proceeds (i.e., the number of shares offered times theoffer price). The free float is the fraction of shares offered at the IPO. Underwriter reputation is measuredby the average rank of the lead (and co-lead) investment bank in terms of its number of New Market leadbank mandates and total New Market IPO volume. Ranks are assigned such that higher market share resultsin higher ranks. The index return before the IPO is measured as the return of the NEMAX All Share indexon 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.


appears to be smaller for U.S. GAAP firms, the differences in the means andmedians between IAS and U.S. GAAP firms are statistically not significant.However, these univariate tests do not control for known determinants offorecast 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 forfirm size and include a binary variable for the firm’s standard choice. IfU.S. GAAP and IAS differ in their ability to convey information to financialanalysts, the forecast dispersion for IAS and U.S. GAAP firms is expected todiffer, even though the direction is ambiguous (Basu et al. [2000]).

Because of low data availability, I estimate regressions for 2000 only. PanelA of table 4 reports these regression results. I find that the differencesin forecast dispersion between IAS and U.S. GAAP firms are statistically

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insignificant after controlling for analyst following, volatility, and firm size.Thus, the results for forecast dispersion corroborate earlier results for thespread and turnover.

Another variable commonly associated with information asymmetry is thelevel 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 IASand U.S. GAAP firms exhibit significant differences in the extent of IPOunderpricing. If U.S. GAAP is superior in its ability to reduce informationasymmetries or represents a stronger commitment to disclosure, I expectfirms using U.S. GAAP to exhibit lower underpricing than firms employingIAS.

Univariate tests indicate that the differences in the means (38.2% and35.6%) 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, Icontrol for offer size, the free float at the IPO, the underwriter’s reputation,and the index return before the IPO. Underpricing generally decreases inthe 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 theUnited States. Similarly, the predicted sign of the free float at the IPO isambiguous and depends on the underpricing theory (e.g., Jenkinson andLjungqvist [2001, pp. 79, 129]). In my context, free float likely controls forrationing and oversubscribed issues. Again, I include industry dummies anda binary variable for the firm’s standard choice.

Panel B of table 4 reports the regression results for the sample used inthe microstructure tests (except for seven firms with missing data). I findthat the differences in underpricing between IAS and U.S. GAAP firms aresmall and statistically insignificant. Thus, the results for IPO underpricingcorroborate earlier results. Similar results are obtained from IPO valuationregressions (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 statisticallyinsignificant.31

The findings for the IPO underpricing and valuation regressions alsomitigate the concern that firms’ reporting choices indirectly influence themarket-based control variables in the microstructure tests. The issue is thatmarket-based control variables (e.g., firm value) could absorb effects that thereporting dummy is meant to capture, making it harder to find significant

30 The extant literature provides various explanations for underpricing relying on some formof 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 theymight be affected by firms’ GAAP choices. The results are not materially altered and thedummy remains insignificant.


differences between IAS and U.S. GAAP firms. But as the IPO underpricingand valuation regressions do not rely on (firm-specific) market-based con-trol variables, they are not as prone to this problem and the dummy variablelikely 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, asNew Market firms choose between the two standards, the previous results maysuffer from selection bias. Thus, I estimate two-stage procedures to checkfor selection bias.

Second, firms’ standard choices provide some additional evidence on thequality of the two standards. The fact that two standards compete in theNew Market suggests that firms trade off the costs and benefits of choosingIAS and U.S. GAAP.33 Therefore, firms’ standard choices are likely to reflect(among other things) the quality and capital market benefits of the twocompeting standards. Moreover, the analysis may shed some light on otherfactors governing the choice between IAS and U.S. GAAP.

Thus far, the costs and benefits of choosing IAS and U.S. GAAP are notwell understood. There is little empirical research. Peemoller, Finsterer, andNeubert [1999] survey 26 New Market firms about their standard choices.The responses suggest that competitors’ standard choices and an existingor intended U.S. listing are key factors in the decision.

According to a more extensive survey conducted by KPMG [2000], CFOsof large European corporations view implementation costs and access tocapital markets as the key factors influencing standard choice. About two-thirds of the respondents consider IAS to be cheaper to implement, whereasthey regard U.S. GAAP as preferable in terms of access to capital markets.KPMG [2000, p. 15], however, points out that the latter position “almostcertainly reflects the SEC’s requirement for foreign companies to present areconciliation 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 ofIAS and U.S. GAAP. The survey finds that about 50% of the respondents rateboth standards as being of high quality and close to 50% of the respondentssee 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 seeminglyunrelated 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 IASand U.S. GAAP firms are close and that I am unable to reject the null hypothesis for a singlecoefficient. These findings suggest that indirect effects on the control variables are likely to beimmaterial in my sample.

33 It is interesting that the split between IAS and U.S. GAAP has been roughly half and halfthroughout the history of the New Market.

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standard choice. That is, respondents seem more concerned with the overallimplications of their decision than with specific accounting issues (KPMG[2000, p. 3]).

The extant empirical literature on voluntary disclosures provides furtherguidance 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 thecontext of this study because if U.S. GAAP are in fact of higher quality thanIAS, the determinants identified in these prior studies should also explainthe choice of U.S. GAAP by New Market firms.34

Based on the extant literature, firm size, current and future financingneeds, and firm performance emerge as the main determinants of corporatedisclosures. The first two are generally positively associated with additionaland higher quality disclosures, whereas the sign of firm performance maydepend on the context and the type of information. In addition, foreignlistings are generally positively associated with corporate disclosures (e.g.,Saudagaran and Meek [1997]). Thus, provided that U.S. GAAP reportingprovides 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 theiraccounting 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 proxyfor financing needs, I use the forecasted average sales growth provided atthe time of the IPO. In addition, I control for the firm’s ownership structureusing the free float at the IPO. Firm performance is measured by the firm’soperating margin in the fiscal year before the IPO. Finally, I control for thefirm’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 negativecoefficient. 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 othercontext. For instance, Harris and Muller [1999] examine the decision of non-U.S. firms toadopt IAS and list in the United States. Leuz and Verrecchia [2000] analyze the decision ofGerman 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 theUnited States in the future. To the extent that capital markets anticipate future U.S. listing, myresults are biased in favor of U.S. GAAP firms. That is, the absence of a proxy for the propensityto list in the U.S. makes it easier to reject the null and hence does not explain the insignificanceof the U.S. GAAP variable.

36 In an earlier version, I reported the frequency of Big 5 auditors and included a Big 5dummy variable in the probit model. However, the fraction of Big 5 auditors is not significantlydifferent for IAS and U.S. GAAP firms, and the dummy is not significant in the probit model.


T A B L E 5Standard Choice and Control for Self-Selection

Panel A: Analysis of standard choice in the New Marketa

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 −0.244Firm size (+) 0.234 0.851 0.094 0.851Sales growth (+) 3.791∗∗ 2.188 1.144∗∗∗ 2.587Free float (+) −1.371 −0.928 −0.744∗ −0.820Operating margin (+/−) −1.271 −0.789 0.244 1.775Firm age (+/−) −0.005 −0.188 0.020 1.542Industry dummies Included Included

McFadden R2 0.293 0.077Likelihood ratio statistic 22.574 19.082

Panel B: Spread and turnover regressions controlling for self-selectionb

Bid-Ask Share TurnoverSpread 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. R2 0.759 0.357F -statistic 93.773∗∗∗ 17.385∗∗∗

aPanel A presents coefficients and z-statistics from probit regressions using the samples for 1999 and2000, but excluding firms with missing data. The dependent variable is binary indicating the accountingstandard choice (U.S. GAAP = 1). The sample for 1999 (2000) comprises 31 (90) IAS and 25 (88) U.S. GAAPfirms. Financial data are obtained from IPO documents. Firm size is the natural logarithm of total sales inthe fiscal year before the IPO. Sales growth is a proxy for financing needs and measured by the forecastedaverage sales growth over the next three years as provided at the time of the IPO. The free float is measuredat the IPO. The firm’s operating margin is operating income (EBIT) divided by total sales and measured inthe fiscal year before the IPO. Firm age is the number of years since the incorporation. Industry dummiesare based on the classification in panel B of table 1. Expected signs for the variables are in parentheses.

bPanel B is based on the two-stage model outlined in section 6. It presents the coefficients and z-statisticsfrom the second stage. Standard errors are adjusted following Maddala [1983]. The dependent variableis in the second (last) column is the percentage spread (percentage turnover). The specification is loglinear as in table 3. U.S. GAAP is a binary variable indicating the accounting standard choice. Firm size isthe average market capitalization. Share turnover is the average daily trading volume divided by the dailymarket capitalization. Volatility is the standard deviation of daily returns. Free float is equal to 1 minus thepercentage of shares closely held. Index inclusion is a binary variable indicating that the firm is included inthe NEMAX 50 index. The inverse Mills ratio is computed from the probit model in panel A. For furtherdetails on the regression variables, see table 2. Expected signs for the variables are in parentheses.


468 C. LEUZ

the United States in the future and therefore retain a larger fraction of thefirm. 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 findingis consistent with the perception that U.S. GAAP is preferable for firms withlarge future financing needs because it allows them to tap into the U.S.capital markets (KPMG [2000]). As mentioned before, this finding may bea reflection of the SEC requirements and not necessarily of the standardquality. 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 variablesare chosen based on the hypothesis that the choice of U.S. GAAP leads tohigher quality disclosures. If, however, the two standards are either compa-rable or do not affect disclosure quality, as my earlier results suggest, I wouldnot expect such variables to have high explanatory power. Furthermore, theresults 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, andGoldberger [1980], Maddala [1983]). The role of the first stage is to con-trol for self-selection. The second stage estimates the association between thespread (turnover) and the firm’s reporting choice as well as other firm char-acteristics taking into account that the reporting variable is endogenous. Toimplement this model, I estimate inverse Mills ratios with the probit regres-sions and include them in the spread and turnover regressions to accountfor 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 spreadand turnover based on the sample for 2000. The results for 1999 are qualita-tively similar. Overall, the coefficients and significance levels of the variablesare not materially different from those reported in table 3. In particular, theU.S. GAAP coefficient remains insignificant in all regressions. Thus, selec-tion bias does not appear to be a severe problem. This conclusion obviouslyhinges on the ability of the probit model to control for self-selection andour understanding of firms’ standard choices.

8. Conclusions

This study is motivated by the global accounting debate about IAS andU.S. GAAP. The debate focuses primarily on comparisons of the stipulatedaccounting methods per se. There is, however, little empirical evidence onthe standards’ economic consequences in capital markets. This study con-tributes a market-based test to this debate. I investigate whether firms usingU.S. GAAP vis-a-vis IAS exhibit differences in several proxies for informa-tion asymmetry. The study exploits the requirement that firms trading in


Germany’s New Market must choose between IAS and U.S. GAAP for finan-cial reporting purposes but are subject to the same regulatory environmentotherwise. Thus, other institutional factors such as listing requirements andenforcement of accounting standards are held constant.

In this setting I find that the differences in the bid-ask spreads and shareturnover between IAS and U.S. GAAP firms are economically and statisticallyinsignificant. Several robustness checks and subsequent analyses of analystforecast dispersion, IPO underpricing, IPO valuation, and firms’ standardchoices provide corroborating evidence. Thus, at least in the New Market,IAS and U.S. GAAP firms do not exhibit significant differences in severalinformation asymmetry proxies. These findings do not support claims thatU.S. GAAP produce financial statements of higher informational qualitythan do IAS.

The results are consistent with at least two interpretations. Based on theview that accounting standards have major consequences in capital markets,the results suggest that IAS and U.S. GAAP are comparable in reducinginformation asymmetries. However, the findings are also consistent with theinterpretation that, despite differences in the standards, New Market firmsexhibit similar accounting quality precisely because firms face similar marketforces and institutional factors, resulting in similar reporting incentives. Thisview relies on recent findings that accounting quality is largely determinedby market forces and institutional factors, rather than accounting standards(e.g., Ball, Robin, and Wu [Forthcoming]) The explanation is that firmscan exceed and to some extent circumvent mandated reporting standards,thereby reducing their influence on observed accounting and disclosurequality.

Finally, although confining attention to New Market firms offers severaladvantages in research design, the setting also has limitations. The resultsshould therefore be interpreted cautiously bearing in mind that the samplechoice could reduce test power, the results need not extend to other firmsand settings, and that the study does not directly address policy questionsfaced by national standard setters.

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