Journal of Accounting Research Vol 41 No June 2003 Printed in U.S.A IAS Versus U.S GAAP: Information Asymmetry–Based Evidence from Germany’s New Market CHRISTIAN LEUZ∗ Received October 2001; accepted November 2002 ABSTRACT Motivated by the debate about globally uniform accounting standards, this study investigates whether firms using U.S generally accepted accounting principles (GAAP) vis-` -vis international accounting standards (IAS) exhibit difa 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 microstructure, 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 Ră der, Robert Verrecchia, and especially Ray Ball and the anonyo mous referee This paper has benefited from presentations at the American Enterprise Institute, University of California at Berkeley, Columbia University, Harvard University, J W Goethe Universită t Frankfurt, MIT, University of Michigan, Stanford University, Tilburg University, the a EAA Meetings (Munich) and the EFA Meetings (Barcelona) I would also like to thank Uwe Schweickert (Deutsche Bă rse), Peter Gomber (Deutsche Bă rse), Jă rg Hueber (KPMG), Rainer o o o Jă ger (PWC), and IBES for generously providing data for this study, and Tobias Herwig for his a 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 consequence for information asymmetry and market liquidity These findings not support widespread claims that U.S GAAP produce financial statements of higher informational quality than IAS 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 standards (IAS) This debate, which is summarized in section 2, 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 (see also Pownall and Schipper [1999]) In this article I investigate whether firms using U.S GAAP vis-` -vis IAS a exhibit cross-sectional differences in several proxies for information asymmetry, 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 standards 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 different 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 comparison 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, setting statistical significance aside, the effect of U.S GAAP reporting is less than 3% of the percentage spread Next, I examine analysts’ forecast dispersion and initial public offering (IPO) underpricing as alternative proxies for information asymmetry and find that the differences are also statistically 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 standards 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 asymmetries 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 quality is largely determined by firms’ reporting incentives created by market forces and institutional factors rather than by accounting standards (in particular, Ball, Robin, and Wu [Forthcoming], Ball and Shivakumar [2002]) Based on this view, IAS and U.S GAAP firms in the New Market are expected to exhibit similar accounting quality, despite differences in the standards, 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 holding 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 sketches the global accounting debate and summarizes prior empirical results Section describes Germany’s New Market Section delineates the research design and section presents the results for bid-ask spreads and share turnover Section considers alternative information asymmetry proxies and 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 examines determinants of firms’ standard choices Section concludes the paper 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 accounting 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 interpretation 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] conducts a detailed case study computing earnings and shareholders’ equity for eight companies under both standards He concludes that firms complying with revised IAS provide accounting measures that are essentially consistent with U.S GAAP and that, based on his study, there is no compelling 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 perceived as being too detailed and too complex IAS opponents, although acknowledging that IAS have improved considerably, argue that many important differences between the two standards 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, measurement, 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 comparability and quality of foreign GAAP relative to U.S GAAP (e.g., Amir, Harris, and Venuti [1993]) Using an information-asymmetry approach, which encompasses 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 accounting standards Harris and Muller [1999] examine Form 20-F reconciliations 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] examine 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 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 Investor , 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 Capitalism,” The Dividend, Spring 1999, pp 22–25 The International Forum on Accountancy Development (www.ifad.net) provides updated comparisons See E MacDonald, “U.S Accounting Board Faults Global Rules,” Wall Street Journal, October 18, 1999, p A1 Davis-Friday and Rueschhoff [2001] examine seven firms before and after the IASC’s Comparability Project and find that IAS net income and shareholders’ equity are more significantly related to market value after the revision of IAS Besides, prior research provides little evidence that investors actually use Form 20-F reconciliations 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 not control for potentially confounding listing, enforcement, or other institutional effects Moreover, the tests focus solely on summary accounting measures and hence 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 accounting standards (e.g., Ball, Robin, and Wu [Forthcoming], Leuz, Nanda, and Wysocki [Forthcoming]) These findings suggest that standards per se not have a major impact on accounting quality and that the global accounting debate focuses perhaps too much on the standards Thus, based on the prior literature, the economic substance of the differences between IAS and U.S GAAP remains an open and largely empirical question 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 companies 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 However, along with other growth and technology markets, the New Market suffered a severe downturn in recent years Responding to this market trend, Deutsche Bă rse decided to reorganize its markets and stop singling out o 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 beyond 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 See, for example,“European Stockmarkets: A German Coup,” The Economist, January 9, 1999, pp 69–71; R Zimmermann, “Eine Flasche Champagner zum dritten Geburtstag,” Financial Times Deutschland, March 9, 2000, p 20; “Amerikas Anleger werden vielfă ltig geschutzt, a ă Frankfurter Allgemeine Zeitung , Septermber 5, 2001, p 208; “Neuer Markt,” Frankfurter Allgemeine Zeitung (Supplement), March 6, 2001 See “Neuer Markt Closure, Comment & Analysis,” Financial Times, September 27, 2002, p 11 10 The Deutsche Bă rse tightened the rules several times to address problems as they became o 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 management 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 minimum 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 prepare 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 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 fur hohe Transparenz am ă Neuen 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 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 marketmaker 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 sponsor performance (since October 1999) and publish ratings (since January 2000) Prior studies suggest that sponsors have a stabilizing, but not dominating, role in the New Market, and in particular they facilitate larger trades (Theissen [1998], Gerke and Bosch [1999]) Research Design and Information Asymmetry Proxies Economic theory suggests that information asymmetries between potential buyers and sellers of firm shares introduce adverse selection into secondary 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 recognition, measurement, and footnote disclosures Consistent with these hypotheses, Welker [1995], Healy, Hutton, and Palepu [1999], and Leuz and Verrecchia [2000] provide evidence that information asymmetry and liquidity proxies are associated with firms’ disclosure and accounting policies Furthermore, security market regulators emphasize the role of highquality accounting standards in leveling the playing field among investors and increasing investor confidence, that is, in reducing information asymmetries 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, http://deutsche-boerse.com/nm/ IAS VERSUS US GAAP 453 asymmetry and higher market liquidity than firms using IAS If the differences between IAS and U.S GAAP firms turn out to be insignificant, then either IAS and U.S GAAP are comparable in reducing information asymmetries, consistent with the argument of IAS proponents, or standards 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 Market firms that are incorporated in Germany and that not trade abroad For these firms, country- and market-specific factors, such as the enforcement of accounting standards and nonaccounting disclosure requirements, are held constant Furthermore, consolidated IAS or U.S GAAP reports not have immediate tax or dividend implications In Germany, taxation and legal dividend restrictions are not based on consolidated (or group) financial 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 Bă rse kindly provided data from June 1, 1999, to July 31, 1999, o 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 average 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 selection 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 supports the choice of turnover as an inverse proxy for information asymmetry For instance, Easley et al [1996] show that the probability of informed trading is decreasing in trading volume and Grammig, Schiereck, and Theissen [2000] confirm their findings for the regular German market segment 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 environment.20 In addition, I eliminate 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 Bă rse and a registration for the o 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 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 coefficient 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 extant 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 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 comparable 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 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 capitalization 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 liquidity for U.S GAAP firms Following the spread model, I use a log-linear specification The results, 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 Information Asymmetry–Based Comparison of IAS and U.S GAAP 1999 (n = 69) 2000 (n = 195) Panel A: Analysis of bid-ask spreads of IAS versus U.S GAAP firms Constant 2.935∗∗∗ 2.123∗∗∗ (8.040) (13.097) U.S GAAP (−) −0.018 −0.022 (−0.402) (−1.013) Firm size (−) −0.273∗∗∗ −0.238∗∗∗ (−12.449) (−16.662) Share turnover (−) −0.210∗∗∗ −0.160∗∗∗ (−3.658) (−9.873) Volatility (+) 0.256∗∗∗ 0.248∗∗∗ (2.879) (6.577) Free float (−) −0.189∗∗∗ −0.120∗∗∗ (−3.078) (−2.451) Adj R F -statistic 2.095∗∗∗ (10.143) −0.001 (−0.033) −0.245∗∗∗ (−14.804) −0.182∗∗∗ (−6.416) 0.265∗∗∗ (3.942) −0.136∗∗ (−2.308) 0.782 139.851∗∗∗ 0.817 68.715∗∗∗ Panel B: Analysis of turnover of IAS versus U.S GAAP firms Constant 1.950∗∗ 2.892∗∗∗ (2.298) (5.894) U.S GAAP (+) 0.007 −0.088 (0.069) (−0.972) Firm size (+/−) 0.036 −0.089∗∗ (0.700) (−2.375) Volatility (+) 0.572∗∗ 1.289∗∗∗ (2.485) (8.891) Free float (+) 0.644∗∗∗ 0.819∗∗∗ (4.512) (6.005) Index inclusion (+) 0.278∗∗ 0.183∗ (2.191) (1.775) 2.119∗∗∗ (2.686) −0.012 (−0.087) −0.119∗∗ (−2.009) 1.105∗∗∗ (5.361) 0.560∗∗∗ (2.805) 0.281 (1.547) Adj R F -statistic 0.752 42.188∗∗∗ 2000 With One-Year Listing (n = 77) 0.324 7.528∗∗∗ 0.394 26.268∗∗∗ 0.381 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 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 Expected signs for the variables are in parentheses ∗ p < (two-sided t-test); ∗∗ p < 05 (two-sided t-test); ∗∗∗ p < 01 (two-sided t-test) Panel B of table reports the coefficients and t-statistics for OLS regressions with White-corrected standard errors The R 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 IAS firms That is, the regressions 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 assumption is critical for the link between the quality of accounting standards and information asymmetry The second concern is that, even if I have appropriately controlled for all other factors determining information asymmetry 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 additional firm characteristics is to control for industry effects because firms in the same industry are likely to exhibit similar firm characteristics In addition, Chordia, Roll, and Subrahmanyam [2000] demonstrate industrywide liquidity effects I create seven industry dummies based on the classification in panel B of table Introducing them into the models does not materially change the coefficients or the t-statistics of the spread or turnover regressions reported in table 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 effect 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 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 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 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 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 financial 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 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 coefficient 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 nature of its firms I therefore set statistical insignificance aside and gauge the economic magnitude of the marginal effect of U.S GAAP reporting.28 Evaluating 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 rating by 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 differences 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 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 dispersion of IBES forecasts in the fifth month after the fiscal year-end to ensure that the firm’s latest annual financial statements and the first quarterly report are available at the time of the analysis Table provides descriptive 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 Alternative Proxies for Information Asymmetry Panel A: Analysis of Forecast Dispersion Constant U.S GAAP (+/−) Volatility (+) Analyst following (+) Firm size (−) Industry dummies R2 Adj F -statistic Forecast Dispersion in 2000 (n = 128) 0.048 (0.391) −0.033 (−1.031) 2.702∗∗ (2.206) 0.120∗∗∗ (3.838) −0.014 (−0.920) Included 0.148 3.003∗∗∗ IPO Underpricing (n = 188) 0.526∗∗ (2.028) U.S GAAP (−) −0.027 (−0.509) Offer size (−) −0.095∗∗ (−2.514) Free float (+/−) −0.005∗ (−1.755) Underwriter reputation (+/−) 0.003 (1.306) Index return before IPO (+) 0.741∗∗∗ (7.369) Industry dummies Included Panel B: Analysis of IPO Underpricing Constant Adj R F -statistic 0.285 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 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 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 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 Expected signs for the variables are in parentheses ∗ p < (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 not control for known determinants of forecast dispersion Following Alford and Berger [1999], I control for the firm’s analyst following, 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 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 disclosures 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 not control 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 prediction 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 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 reputation, 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 not rely on (firm-specific) market-based control variables, they are not as prone to this problem and the dummy variable likely captures all reporting consequences.32 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 Peemă ller, Finsterer, and o 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 twothirds 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 differences 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 analyze firms’ decisions to provide voluntarily more and higher quality information (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 performance (+/−) 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 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 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 auditors and included a Big dummy variable in the probit model However, the fraction of Big 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 Standard Choice and Control for Self-Selection Panel A: Analysis of standard choice in the New Marketa 1999 (n = 56) U.S GAAP ( = 1) Constant Firm size (+) Sales growth (+) Free float (+) Operating margin (+/−) Firm age (+/−) Industry dummies Coefficients z-statistics −1.849 −0.957 0.234 0.851 3.791∗∗ 2.188 −1.371 −0.928 −1.271 −0.789 −0.005 −0.188 Included McFadden R Likelihood ratio statistic 2000 (n = 178) U.S GAAP ( = 1) Coefficients z-statistics −0.203 −0.244 0.094 0.851 1.144∗∗∗ 2.587 −0.744∗ −0.820 0.244 1.775 0.020 1.542 Included 0.293 22.574 Panel B: Spread and turnover regressions controlling for self-selectionb Bid-Ask Spread 2000 (n = 178) Constant U.S GAAP (−) Firm size (−) Share turnover (−) Volatility (+) Free float (−) Inverse Mills ratio Adj R F -statistic 2.050∗∗∗ (14.268) 0.010 (0.133) −0.233∗∗∗ (−23.145) −0.160∗∗∗ (−8.479) 0.237∗∗∗ (5.624) −0.115∗∗∗ (−2.835) −0.018 (−0.381) 0.759 93.773∗∗∗ Constant U.S GAAP (+) Firm size (+/−) Volatility (+) Free float (−) Index inclusion (+) Inverse Mills ratio 0.077 19.082 Share Turnover 2000 (n = 178) 2.702∗∗∗ (4.696) −0.035 (−0.106) −0.088∗ (−1.849) 1.242∗∗∗ (8.113) 0.828∗∗∗ (5.021) 0.180 (1.250) −0.026 (−0.123) 0.357 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 Expected signs for the variables are in parentheses b Panel B is based on the two-stage model outlined in section 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 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 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 Expected signs for the variables are in parentheses ∗ p < (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 a reflection 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 disappointing, 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 comparable or 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 control for self-selection The second stage estimates the association between the spread (turnover) and the firm’s reporting choice as well as other firm characteristics taking into account that the reporting variable is endogenous To implement this model, I estimate inverse Mills ratios with the probit regressions 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 insignificant in my spread and turnover regressions The p-values range between 0.403 and 0.902 Panel B of table presents the results for the spread and turnover based on the sample for 2000 The results for 1999 are qualitatively similar Overall, the coefficients and significance levels of the variables are not materially different from those reported in table In particular, the U.S GAAP coefficient remains insignificant in all regressions Thus, selection 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 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 contributes a market-based test to this debate I investigate whether firms using U.S GAAP vis-` -vis IAS exhibit differences in several proxies for informaa 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 financial 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, 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