Foreign Private Issuers' Application of IFRS Around the Elimination of the 20-F Reconciliation Requirement

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The International Journal of Accounting 48 (2013) 54 – 83

Foreign Private Issuers' Application of IFRS Around the Elimination of the 20-F Reconciliation Requirement☆ Tzu-Ting Chiu, Yen-Jung Lee ⁎ Department of Accounting, National Taiwan University, Taiwan Received 15 February 2011

Abstract This study examines how the elimination of the 20-F reconciliation requirement affects the quality of accounting data prepared by cross-listed firms that report under IFRS as promulgated by the IASB (hereafter CL IFRS firms). Using IFRS-adopting firms that are not cross-listed in the U.S. (hereafter NCL IFRS firms) as the control sample, we find that CL IFRS firms experience a decrease in the magnitude of accounting discretion, a change in the asymmetric timeliness of earnings, and an improvement in the value relevance of reported earnings between the pre- and the post-elimination periods. These results suggest that the SEC's previous reconciliation requirement may have an unintended negative effect on CL IFRS firms' incentives in the application of IFRS. Comparing accounting quality under IFRS and U.S. GAAP in the post-elimination period, our additional analysis shows that the quality of accounting data prepared using IFRS by CL IFRS firms is comparable to that prepared using U.S. GAAP by U.S. firms, except that IFRS-based numbers exhibit less earnings asymmetry than U.S. GAAP-based numbers. © 2013 University of Illinois. All rights reserved. JEL classification: G15; G18; M41; M48 Keywords: 20-F reconciliation; IFRS; U.S. GAAP; Accounting quality

☆ We thank two anonymous reviewers, the editor, and workshop participants at National Taiwan University (NTU), NTU-Peking University joint workshop, 2010 American Accounting Association Annual Meeting, and 2011 Financial Accounting and Reporting Section/International Accounting Section Midyear Meeting for helpful comments. Yen-Jung Lee gratefully acknowledges the financial support from the Taiwan National Science Council. ⁎ Corresponding author at: Department of Accounting, National Taiwan University, 1, Roosevelt Road, Sec. 4, Taipei 10617, Taiwan. Tel.: +886 2 3366 9782; fax: +886 2 2363 8038. E-mail addresses: [email protected] (T.-T. Chiu), [email protected] (Y.-J. Lee). 0020-7063/$ - see front matter © 2013 University of Illinois. All rights reserved. http://dx.doi.org/10.1016/j.intacc.2013.01.006

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1. Introduction This paper investigates whether the elimination of the reconciliation requirement affects the quality of accounting information for cross-listed firms that report under International Financial Reporting Standards (IFRS) as issued by the International Accounting Standards Board (IASB) (hereafter referred to as CL IFRS firms). In December 2007, the U.S. Securities and Exchange Commission (SEC) issued a final rule that permitted foreign private issuers to submit financial statements prepared under the IASB's version of IFRS without reconciliation to U.S. generally accepted accounting principles (U.S. GAAP) for fiscal years ending after November 15, 2007 (SEC, 2007a). 1 Much of the debate on this regulatory change engages the usefulness of the reconciliation (Hopkins et al., 2008; Jamal et al., 2008). 2 Accordingly, most of the relevant research (e.g., Jiang, Petroni, & Wang, 2010; Kim, Li, & Li, 2012) focuses on this front, which shows no significant impact on information asymmetry and market liquidity. However, we find some evidence that some CL IFRS firms changed their accounting policies around the rule change, suggesting that the reconciliation requirement may influence the application of IFRS by CL IFRS firms. 3 Therefore, we fill this gap in the literature by examining whether the quality of IFRS-based numbers changes around the rule change. Prior literature (e.g., Leuz, 2006) suggests that large reconciliation differences revealed in 20-F filings might be challenged by local authorities and raise concerns among investors. To minimize the reconciliation, CL IFRS firms tend to choose within IFRS the accounting methods that most conform to U.S. GAAP. 4 Once the reconciliation requirement is removed, the materiality of the reconciliation is no longer a concern for CL IFRS firms. CL IFRS firms are thus free to deviate from U.S. GAAP and are able to make accounting choices that better communicate firm performance without constraints. However, the removal of the reconciliation requirement also results in the loss of required information (i.e., U.S. GAAP reconciliation and related U.S. GAAP disclosures) and a reduced level of SEC scrutiny (i.e., review of IFRS reports only). CL IFRS firms could have incentives to engage in opportunistic reporting in light of the reduced disclosure and regulatory scrutiny. Hence, whether eliminating the reconciliation requirement leads to improved or deteriorated accounting quality is an empirical question. To investigate empirically, we compare the characteristics of IFRS-based accounting data before and after the regulatory change to see the changes between the pre- and post-elimination periods. We measure the quality of IFRS-based numbers by the following three accounting attributes: (1) accounting discretion contained in reported earnings, as measured by the magnitude of discretionary working capital accruals; (2) asymmetric timely loss recognition, as described in Basu (1997); and (3) value relevance of accounting numbers, as proxied by the We use the term “foreign private issuers” interchangeably with the broad term “cross-listed firms” throughout the paper. 2 See Section 2 for a more detailed discussion of the responses to the SEC's decision to eliminate the reconciliation requirement. 3 Examples of such accounting changes are provided in Section 2. 4 In this paper, we only focus on how managers' difference-minimizing incentives affect the quality of accounting data. As to which part of the reconciliation the firm intends to minimize, line items or bottom-line numbers, we leave it as an open empirical question. 1

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earnings response coefficient (ERC). Because the properties of accounting data have been shown to be correlated with institutional environments (Ball, Robin, & Wu, 2003; Bradshaw & Miller, 2008; Burghstahler, Hail, & Leuz, 2006) and cross-listing status (Lang, Raedy, & Yetman, 2003; Lang, Smith Raedy, & Wilson, 2006), we use a matched sample design to control for the potential confounding effects. To rule out the possibility that our findings are driven by either the evolution of IFRS over time or changes in the local macro-environment as opposed to the regulatory change of interest, we match CL IFRS firms with a sample of IFRS-adopting firms that are not cross-listed in the U.S. (hereafter referred to as NCL IFRS firms) based on country, year, industry, and sales growth. 5 Relative to NCL IFRS firms, we find that CL IFRS firms exercise less discretion over accounting earnings and engage in more asymmetric recognition of losses and their reported earnings are more value relevant after the reconciliation requirement is lifted. We interpret the results as suggesting that the elimination of the reconciliation requirement enables CL IFRS firms to choose accounting policies that better reflect their underlying business economics, resulting in more informative accounting information. Our results also imply that the U.S. GAAP reconciliation that the SEC required until recently might have the unintended consequence of impairing CL IFRS firms' application of IFRS by precluding them from communicating their economic performance through accounting choices. Since large reconciliation differences are more likely to trigger regulatory scrutiny when local monitoring is more intense, firms in countries with stronger monitoring would have greater concern about the materiality of the reconciliation, which gives them more incentives to minimize the reconciliation differences. Therefore, we expect that the effect of the rule change on the quality of IFRS-based numbers is more pronounced for CL IFRS firms subject to stronger local monitoring. We use the public enforcement index constructed by La Porta, Lopez-De-Silanes, and Shleifer (2006) as a proxy for the level of local monitoring. Partitioning our sample into high and low public enforcement subsamples, we find that our findings are primarily driven by firms from high enforcement countries. These findings suggest that CL IFRS firms subject to more intense local monitoring are more likely to bias accounting choices toward those closer to U.S. GAAP to reduce the materiality of the reconciliation and thereby lower the expected costs arising from regulatory scrutiny. Recently, the SEC has been deliberating whether to permit or require the use of IFRS by U.S. issuers. 6 A key consideration underlying the SEC's deliberation is whether accounting numbers reported under IFRS are of comparable quality to those reported under U.S. GAAP. Although there is a growing literature comparing accounting quality under IFRS and U.S. GAAP, prior studies suffer from some sample or design limitations, which prevent them from providing relevant evidence on the potential application of IFRS by U.S. firms. 5 In our supplementary analyses, we also use a matched sample of U.S. firms to rule out the alternative explanation that our findings are driven by the contemporaneous changes in the U.S. macro-environment. We obtain qualitatively similar results using this alternative control sample. 6 In August 2007, the SEC issued a concept release on allowing U.S. issuers to prepare financial statements based on IFRS (SEC, 2007b). Further, in August 2008, the SEC issued a proposed roadmap that could lead to mandatory transition to IFRS for U.S. issuers from 2014 (SEC, 2008). However, the SEC's latest work plan issued in February 2010 suggests that the first time adoption of IFRS for U.S. issuers would be approximately in 2015 or 2016 under the premise that the SEC determines whether to incorporate IFRS into the U.S. financial reporting system in 2011.

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Accounting quality is determined largely by firms' reporting incentives, which are affected by country-specific institutional factors. Thus, the results from studies examining the application of IFRS by non-U.S. firms that are not traded in the U.S. markets might not pertain to U.S. publicly traded companies (e.g., Barth, Landsman, Lang, & Williams, 2007, 2010). Moreover, IFRS has been revised substantially since the early 2000s as a result of the Financial Accounting Standards Board (FASB) and IASB's joint convergence efforts after the “Norwalk Agreement,” suggesting that the results from studies examining periods that predate the Norwalk Agreement might not be generalized to recent years (e.g., Bartov, Goldberg, & Kim, 2005; Leuz, 2003). 7 Compared with sample firms used in prior research, CL IFRS firms are more similar to U.S. firms in terms of investor clientele and product market interactions. In addition, CL IFRS firms are subject to the SEC's jurisdiction and enforcement as are U.S. firms. Using 20-F reconciliations filed by CL IFRS firms for fiscal years 2004–2006, Gordon, Jorgensen, and Linthicum (2008) find that the quality of IFRS-based numbers is comparable to that of U.S. GAAP-based numbers, expect that U.S. GAAP-based numbers exhibit higher value relevance than IFRS-based numbers. However, as we demonstrate in this study, the reconciliation requirement affects the application of IFRS by CL IFRS firms. We therefore believe that accounting quality resulting from applying IFRS by CL IFRS firms after the regulatory change better reflects what would result from the neutral application of IFRS. In the additional analysis, we re-examine the quality of accounting numbers prepared under IFRS and U.S. GAAP using data from the post-elimination period. Our results show that accounting data prepared using IFRS by CL IFRS firms are of similar quality to those prepared using U.S. GAAP by U.S. firms in terms of the magnitude of accounting discretion and value relevance, implying that accounting quality under current IFRS and U.S. GAAP is comparable. We find only weak evidence that U.S. firms engage in more asymmetric recognition of losses than do CL IFRS firms, suggesting that U.S. GAAP-based earnings are more conditionally conservative than IFRS-based earnings. Our paper contributes to the literature in several ways. First, we add to the literature on the unintended consequences of SEC regulation. Unlike prior research focusing mainly on the economic consequences of eliminating the 20-F reconciliation, our results suggest that the reconciliation requirement had an unintended negative effect on firms' reporting incentives, resulting in lower quality accounting information. Second, we extend the literature on the implication of IFRS adoption. We utilize the uniqueness of CL IFRS firms to provide more relevant evidence on the possible use of IFRS by U.S. firms than do prior studies. Third, we provide the latest evidence on the quality of IFRS-based and U.S. GAAP-based numbers. We examine accounting quality under these two sets of standards using the period after the regulatory change in 2007, a period that better reflects the current states of IFRS and U.S. GAAP. The remainder of the paper is organized as follows. Section 2 reviews the relevant literature and develops the hypothesis. Section 3 presents the research design. Section 4 In October 2002, the FASB and IASB signed a Memorandum of Understanding (the “Norwalk Agreement”), which is regarded as a significant step toward the convergence of U.S. GAAP and IFRS. Important initiatives set out by the Agreement include a move to eliminate minor differences between U.S. and international standards, a decision to align the two boards' future work programs, and a commitment to work together on joint projects. 7

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describes the sample and presents the descriptive statistics. Section 5 reports the empirical results and provides supplementary analyses. Section 6 performs the additional analysis of accounting quality under IFRS and U.S. GAAP. Section 7 summarizes and concludes. 2. Related literature and hypothesis development The reconciliation requirement for foreign private issuers dates back to 1982. The SEC requires foreign private issuers that prepare financial statements based on non-U.S. GAAP to reconcile their net income and stockholders' equity to U.S. GAAP as part of 20-F filings. Due to large accounting differences between local GAAP and U.S. GAAP, the reconciliation has long been considered as a significant barrier for foreign private issuers to entry into U.S. capital markets, which imposes considerable costs on foreign firms seeking U.S.-listing (Fanto & Karmel, 1997). As a step toward the goal of a single set of highquality global accounting standards, on November 15, 2007, the SEC voted to allow foreign private issuers to file IFRS financial statements without providing reconciliations to U.S. GAAP. The academic community, however, is divided with respect to the response to the SEC's decision to accept IFRS-based reports from foreign private issuers. The Financial Accounting Standards Committee of the American Accounting Association (AAA) voices support for this regulatory change on the basis that both IFRS and U.S. GAAP meet a minimum quality threshold and there is no conclusive evidence about which set of accounting standards produces superior information (Jamal et al., 2008). It further proposes the extension of the choice of IFRS to U.S. firms because allowing IFRS to compete freely with U.S. GAAP will offer both IASB and FASB timely feedback about the efficacy of their standards, leading to improved accounting standards. In contrast, the Financial Reporting Policy Committee of the Financial Accounting and Reporting Section of the AAA contends that it is too hasty to end the reconciliation requirement because there are still significant differences between U.S. GAAP and IFRS. As a result, comparability problems would exist without the U.S. GAAP reconciliation (Hopkins et al., 2008). 8 The Committee also indicates that empirical evidence (e.g., Chen & Sami, 2008; Henry, Lin, & Yang, 2009) shows that 20-F reconciliations are decision relevant; thus, the elimination of the reconciliation requirement may result in losses of useful information for investors. Due to the ongoing efforts of the FASB and IASB toward the convergence of financial reporting, the importance of the reconciliation should diminish over time. Using 20-F reconciliations filed by foreign private issuers reporting under the IASB's version of IFRS 8

Common 20-F reconciliation items include income taxes, post-employment benefits (e.g., pensions), and property, plant, and equipment (see the descriptive statistics provided by Gordon et al., 2008 and Henry et al., 2009 for a comprehensive description of reconciliation categories). First, tax differences mainly lie in the recognition of deferred taxes. U.S. GAAP requires firms to recognize deferred taxes for taxable temporary differences arising from the initial recognition of an asset or liability while IFRS does not. Second, a noticeable difference in post-employment benefits is the recognition of actuarial gains and losses. Compared with the corridor approach under U.S. GAAP, IFRS permits any systematic methods for recognition that result in faster recognition of actuarial gains and losses. Finally, the major difference in property, plant, and equipment is the basis of measurement. IFRS allows firms to use either revalued amount or historical cost whereas U.S. GAAP only permits the use of historical cost.

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during 2006 and 2007, Jiang et al. (2010) document that the reconciliation lacks information content just prior to the regulatory change. Their findings imply that canceling the reconciliation requirement does not lead to information losses. Consistent with Jiang et al. (2010), Kim et al. (2012) also find no capital market consequences associated with this rule change. Although the elimination of the reconciliation requirement had no significant impact on information asymmetry and market liquidity for CL IFRS firms, this regulatory change may influence the application of IFRS by CL IFRS firms. We randomly select a sample of 50 20-F filings that CL IFRS firms filed after the rule change and we compare these with the respective prior period 20-Fs filed before the rule change. We find that some firms change their accounting policies around the elimination of the reconciliation requirement, among which a great proportion is related to the fair value adoption permitted under IFRS. For example, in 2008, Portugal Telecom, SGPS S.A. decided to change the accounting principle regarding the measurement of real estate properties and ducts infrastructure from the cost model to the revaluation model. 9 We argue that cross-listed firms may be incentivized to bias accounting choices toward those more conforming to U.S. GAAP under the reconciliation requirement. This is because large differences between local GAAP and U.S. GAAP figures revealed in 20-F reconciliations are likely to be questioned by local authorities and raise concerns among investors (Leuz, 2006). As a result, to avoid these undesirable consequences, firms may intentionally choose within local GAAP the accounting methods that are closer to U.S. GAAP to minimize the magnitude and frequencies of reconciliations. In other words, the reconciliation requirement might provide cross-listed firms with difference-minimizing incentives to make suboptimal accounting choices. 10 Once the reconciliation requirement is eliminated, CL IFRS firms are free to deviate from U.S. GAAP, enabling them to make accounting choices without constraints. In this case, managers could choose accounting methods that better communicate firm performance, leading to IFRS-based accounting numbers better reflective of the underlying business economics. On the other hand, the elimination of the reconciliation requirement also results in a reduced level of disclosure and regulatory scrutiny, which might provide firms with opportunistic incentives. After the reconciliation requirement is eliminated, CL IFRS firms no longer need to provide U.S. GAAP reconciliations and related footnote disclosures in 20-F

9 Other examples include: (1) in 2007, Alcatel-Lucent changed its accounting method of actuarial gains and losses resulting from defined benefit post-employment pension plans from spreading over the service lives of the employees to immediately recognizing in full in the period in which they occur.; and (2) AEGON N.V. disclosed in the 2007 annual report that the company changed its accounting policies for valuing minimum guarantees related to insurance products offered by AEGON The Netherlands from applying a corridor approach to valuing at fair value. 10 Note that we do not mean that choosing accounting methods more conforming to U.S. GAAP leads IFRSbased numbers to be of lower quality. What we are saying is accounting numbers with constraints should be no better than those without constraints. Accounting methods prescribed by U.S. GAAP might be high quality accounting standards but they might not be the best methods that capture CL IFRS firms' underlying business economics. Lang et al. (2006) show that cross-listed firms reconciling to U.S. GAAP exhibit more evidence of earnings management than U.S. firms, revealing the difference in the quality between reconciled U.S. GAAP numbers and genuine ones.

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filings. Instead, they file IFRS reports directly with the SEC. 11 Also, the SEC reviewed reconciliation differences between U.S. GAAP and IFRS and related U.S. GAAP disclosures previously, but it changed to the review of IFRS financial statements after the rule change. Given the decrease of the required information and direct regulation following the elimination of the reconciliation requirement, managers are likely to engage in opportunistic reporting by exploiting the discretion afforded by IFRS, leading to worse accounting quality. Based on the above arguments, the elimination of the reconciliation requirement could either improve or impair the quality of accounting data resulting from the application of IFRS by CL IFRS firms. Therefore, we pose our non-directional hypothesis as follows: Hypothesis. The quality of the accounting reports prepared using IFRS by CL IFRS firms during the period when the reconciliation requirement was effective will be different from that of the period when the reconciliation requirement was eliminated. 3. Research design We investigate changes in the quality of IFRS-based accounting data before and after the removal of the U.S. GAAP reconciliation for CL IFRS firms by conducting three separate tests relating to accounting discretion contained in reported earnings, asymmetric timely loss recognition, and value relevance of accounting numbers (detailed in Sections 3.1–3.3). Panel A of Fig. 1 illustrates our research question and test/control samples used in the empirical analysis. Because firms self-select into cross-listing in the U.S., there might be some factors that are correlated with the cross-listing decision and that also affect the characteristics of accounting data (Lang et al., 2003; Lang et al., 2006). Furthermore, accounting characteristics are influenced by country-specific institutional factors beyond accounting standards (Ball et al., 2003; Bradshaw & Miller, 2008; Burghstahler et al., 2006). Thus, we use a matched sample design to mitigate the concern of these confounding effects. We match CL IFRS firms with a sample of NCL IFRS firms to rule out the alternative explanation that changes in accounting attributes between the pre- and post-elimination periods are driven by the evolution of IFRS or changes in local markets rather than the removal of the reconciliation requirement. 12 To construct the matched sample, we require NCL IFRS firms to be from the same country and with the same industry membership as CL IFRS firms. We then choose the firm that is closest in latest sales growth as the matching 11 We observe that none of our sample firms voluntarily provides U.S. GAAP reconciliations after the rule change, suggesting that the cost of making such disclosures outweighs the benefit. 12 It is empirically difficult to implement the Heckman model in our setting to control for self-selection bias arising from the selectivity of firms into cross-listing. Variables influencing the cross-listing decision such as size, growth, and firm performance also affect our accounting quality proxies. To deal with the potential selectivity, we conduct propensity score matching (PSM) to control for factors that affect the cross-listing decision and accounting quality. First, we run a logit regression of the cross-listing decision on firm size, equity and debt issuance, leverage, asset turnover, and sales growth. We then match, without replacement, a CL IFRS firm with a NCL IFRS firm that has the closest predicted value from the previous regression model within a caliper distance of 3%. Of the 330 CL IFRS firm-years in our initial sample, 278 successfully find their corresponding NCL IFRS matches. Our primary inferences remain unchanged under the PSM approach.

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A) CL IFRS firms (Test sample) vs. NCL IFRS firms (Control sample)

Nov. 15, 2005

Nov. 15, 2007 Pre-elimination period

cf.

Nov. 15, 2009 Post-elimination period

B) CL IFRS firms

Nov. 15, 2005

vs.

U.S. firms

Nov. 15, 2007 Pre-elimination period

Nov. 15, 2009 Post-elimination period

Fig. 1. Research question and test/control samples. Panel A: Comparison of the quality of IFRS-based numbers before and after the regulatory change. Panel B: Comparison of accounting quality under IFRS and U.S. GAAP in the pre-/post-elimination period.

firm. 13 Once a NCL IFRS firm is selected as a match, we include all its available firm-years in our empirical analyses. We use Petersen's (2009) double cluster procedure to allow inter-correlations of residuals across firms or across time. Further, industry, country, and year fixed effects are included in all models to control for industry-, country-, and time-specific omitted variables. 3.1. Accounting discretion contained in reported earnings Leuz (2006) argues that cross-listed firms reconciling accounting numbers to U.S. GAAP are likely to have incentives to minimize the reconciliation differences disclosed in 20-Fs. This could motivate managers to make accounting choices more conforming to U.S. GAAP by exercising discretion over accounting methods/assumptions afforded under IFRS. Due to the limited number of cross-sectional observations in each country–industry– year, we are unable to reliably estimate discretionary accruals using the modified Jones 13 We choose the sales growth match instead of the size match, as measured by the market value of equity (MVE), for the following reasons. First, the link between firms' reported earnings and MVE might be a function of earnings quality, a main focus of this study. Sales growth, on the other hand, is not affected in that manner and seems to be a cleaner measure in our context. Second, the association between growth and accruals is clearer than that between firm size and accruals. Third, and more importantly, CL IFRS firm's size tends to be large because of its multi-national business nature. Hence, it is not easy to find a matching firm of similar size, and using the size match would result in poor matching quality that might bias our inferences.

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model. We therefore rely on the absolute value of working capital accruals, partialling out factors affecting nondiscretionary accounting decisions in the pooled cross-section time-series analysis, to capture the magnitude of managerial discretion over accounting choices. Following Dechow and Dichev (2002), we measure working capital accruals, denoted WCACC, as the sum of increase in accounts receivable, increase in inventory, decrease in accounts payable, decrease in income tax payable, and net change in other accrued liabilities, scaled by lagged total assets. We examine the change in the magnitude of accounting discretion being exercised by managers from the pre- to the post-elimination period by estimating the following regression, pooling all CL IFRS and NCL IFRS sample firm-years: ABSWCACC it ¼ α 0 þ α 1 POST it þ α 2 CLit þ α 3 POST it  CLit þ α 4 ABSðΔSALESit −ΔARit Þ þ α 5 ROAit þ α 6 SIZEit þ α 7 EISSUEit þ α 8 DISSUE it þ α 9 LEV it þ α 10 TURN it þα 11 CFit þ α 12 GROWTH it þ Year dummies þ Country dummies þ Industry dummies þ ε it

ð1Þ

where ABSWCACC is the absolute value of WCACC, POST is an indicator variable set equal to one if firm-year observations are from the post-elimination period and zero otherwise, and CL is an indicator variable that equals one for CL IFRS firm-year observations and zero for NCL IFRS ones. To ensure that we isolate the discretionary component of absolute working capital accruals, we follow Dechow, Sloan, and Sweeney (1995) and control for the absolute value of the change in cash-basis sales scaled by lagged total assets, denoted ABS(ΔSALES − ΔAR), to capture nondiscretionary accruals resulting from the normal course of business. We also control for the firm's accounting performance because nondiscretionary accruals have been shown to be correlated with firm performance (Dechow et al., 1995; Kothari, Leone, & Wasley, 2005). Accounting performance, denoted ROA, is measured by net income divided by lagged total assets. In addition, we follow Lang et al. (2006) and include controls for other factors that are associated with the cross-listing decision and that might influence financial reporting. SIZE is the natural logarithm of year-end market value of equity in millions; EISSUE is the percentage change in common stock; DISSUE is the percentage change in debt; LEV is year-end total liabilities divided by year-end total equity; TURN is sales divided by total assets; CF is annual net cash flow from operating activities scaled by lagged total assets; and GROWTH is the percentage change in sales. We interpret the coefficient on POST as the difference in the magnitude of discretionary working capital accruals between the pre- and post-elimination periods for NCL IFRS firms, the coefficient on POST + POST × CL as the pre- and post-difference in absolute discretionary working capital accruals for CL IFRS firms, and the coefficient on POST × CL as the incremental change in the magnitude of discretionary working capital accruals from the preto the post-elimination period between CL IFRS and NCL IFRS firms. 3.2. Asymmetric timely loss recognition An untabulated finding in Barth et al. (2007) shows that U.S. firms recognize losses in a timelier manner than IAS firms, consistent with the conventional wisdom that financial reporting under U.S. GAAP is more conditionally conservative than that under IFRS.

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Conditional conservatism means that “book values are written down under sufficiently adverse circumstances but not written up under favorable circumstances” (Beaver & Ryan, 2005). This asymmetry gives rise to systematic differences in the timeliness of earnings between bad news and good news, with firms incorporating bad news into earnings in a timelier manner than good news. Following Basu (1997), we infer asymmetric timely loss recognition by relating earnings to stock returns. We measure the difference in the incremental timeliness of bad news over good news (R × DUM) between the pre- and postelimination periods by estimating the following regression separately for CL IFRS and NCL IFRS firms: Eit ¼ α 0 þ α 1 Rit þ α 2 DUM it þ α 3 Rit  DUM it þ α 4 POST it þ α 5 POST it  Rit þ α 6 POST it  DUM it þα 7 POST it  Rit  DUM it þ Year dummies þ Country dummies þ Industry dummies þ ε it

ð2Þ where E is earnings per share excluding extraordinary items scaled by price at the beginning of the year, R is the 15-month buy-and-hold return for the period ending three months after the fiscal year-end, and DUM is an indicator variable set equal to one if the return is negative and zero otherwise. We interpret the coefficient on POST × R × DUM as the change in the degree of asymmetric timeliness of earnings with respect to bad news and good news from the pre- to the post-elimination period. 3.3. Value relevance of accounting numbers Relevance is an important quality that makes accounting information useful for decision making. Since higher quality earnings better reflect a firm's underlying economics, a higher association between stock prices and earnings is anticipated for firms with higher accounting quality (Barth, Beaver, & Landsman, 2001). 14 We use the slope coefficient of the return– earnings model (i.e., ERC) as a proxy for the value relevance of accounting numbers. We measure the magnitude of the ERC by estimating the following regression, controlling for the determinants of the return–earnings relation suggested by previous studies (e.g., Collins & Kothari, 1989; Hayn, 1995; Kormendi & Lipe, 1987; Lipe, 1990): Rit ¼ α 0 þ α 1 Eit þ α 2 POST it þ α 3 Eit  POST it þ α 4 CLit þ α 5 Eit  CLit þ α 6 POST it  CLit þ α 7 Eit  POST it  CLit þ α 8 SIZEit þ α 9 Eit  SIZEit þ α 10 BMit þ α 11 Eit  BMit þα 12 LOSSit þ α 13 Eit  LOSSit þ Year dummies þ Country dummies þIndustry dummies þ ε it

ð3Þ where BM is the book value of equity scaled by the market value of equity and LOSS is an indicator variable taking the value of one if earnings before extraordinary items are negative and zero otherwise. To investigate the difference in the value relevance of accounting data between the pre- and post-elimination periods, we estimate Eq. (3) pooling all CL IFRS and NCL IFRS firm-year 14

With regard to the strengths and weaknesses of inferences based on value relevance, please refer to Barth et al. (2001) and Holthausen and Watts (2001) for in-depth discussions.

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observations. We interpret the coefficient on E × POST as the differential magnitude of ERCs between the pre- and post-elimination periods for NCL IFRS firms, the coefficient on E × POST + E × POST × CL as the pre- and post-difference in the magnitude of ERCs for CL IFRS firms, and the coefficient on E × POST × CL as the incremental change in the magnitude of ERCs from the pre- to the post-elimination period between CL IFRS and NCL IFRS firms. 4. Sample and data Table 1 provides an overview of the sample selection process. We obtain 20-F filings for fiscal years ending between November 16, 2005 and November 15, 2009 via the SEC's EDGAR system, of which 330 firm-years report under IFRS as promulgated by the IASB (referred to as CL IFRS firm-years). 15 , 16 We choose this period because it results in balanced pre- and post-elimination periods, i.e., two years for the pre- and two years for the post-period. Since we focus on the changes in the quality of IFRS-based accounting data from the pre- to the post-elimination period, both CL IFRS and NCL IFRS firms must have at least one pre- and one post-observation to be included in the analysis. 17 When performing the one-to-one matching, we lose 49 firm-years due to the inability to find a NCL IFRS matching firm from the same country, year, and industry and with similar sales growth. After eliminating observations without necessary data on Compustat North America/Global to estimate Eq. (1), we are left with 333 firm-years for the accrual test. Likewise, firm-years without required data on Compustat North America/Global and CRSP to estimate Eqs. (2) and (3) are excluded from our analysis, leaving 480 firm-years for the asymmetric timely loss recognition and value relevance tests. Panel A of Table 2 presents the country breakdown of our sample. 18 In general, CL IFRS firm-years are from a wide range of countries, with the greatest representation from the United Kingdom. Panel B of Table 2 shows the industry breakdown by Global Industry Classification Standard (GICS) sectors. The sample is composed of various industry sectors, with almost half of the sample consisting of firms in the telecommunication services, energy, and materials sectors. Because of the country and industry clustering in our sample, we control for country and industry membership in all of the empirical models. Table 3 reports descriptive statistics on test and control variables used in the analysis. All continuous variables are winsorized at the 1st and 99th percentiles to mitigate the influence 15 In this paper, we define the fiscal years relative to November 15, 2007, the date that the SEC's noreconciliation rule applied to the financial statements prepared using IFRS as issued by the IASB. Fiscal years ending between November 16, 2005 and November 15, 2006 are designated as the fiscal year 2006, and the remaining years are adjusted accordingly. 16 To identify CL IFRS firm-years, we first use Compustat accounting standard item (ACCTSTD) and retain only those coded “DI” (domestic standards generally in accordance with or fully compliant with IFRS) as firm-years reporting under IFRS. We then manually examine 20-Fs of these observations to double-check the accounting standards used in presenting financial statements. 17 This requirement explains why the number of firm-year observations differs slightly between CL IFRS and NCL IFRS samples. 18 We use the location of headquarters rather than the country of incorporation because the firm's choice of the country of incorporation is often out of tax considerations (e.g., Bermuda, British Virgin Islands, and Cayman Islands are well-known tax havens) and thus not as informative as the firm's headquarter location.

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Table 1 Sample selection. Number of firm-years 20-F firm-years that report under IFRS as issued by the IASB (hereafter, CL IFRS firm-years) for fiscal years 2006–2009 a CL IFRS firm-years with corresponding NCL IFRS matching firms CL IFRS firm-years with required data on Compustat to estimate Eq. (1) Plus: Matched NCL IFRS firm-years with required data on Compustat Global to estimate Eq. (1) Total firm-year observations for the accrual test CL IFRS firm-years with required data on Compustat and CRSP to estimate Eqs. (2) and (3) Plus: Matched NCL IFRS firm-years with required data on Compustat Global to estimate Eqs. (2) and (3) Total firm-year observations for the asymmetric timely loss recognition and value relevance tests a

330 281 163 170 333 _ 242 238 480

_

We define the fiscal years relative to November 15, 2007, the date that the SEC ended the U.S. GAAP reconciliation for foreign private issuers reporting under IFRS as promulgated by the IASB. For example, we classify the fiscal years ending between November 16, 2005 and November 15, 2006 as the fiscal year 2006, and the remaining years are adjusted similarly.

of outliers. Relative to NCL IFRS firms, CL IFRS firms have a lower amount of working capital accruals and higher operating cash flow, and their earnings and stock performance are better. Given the matching criteria, CL IFRS and NCL IFRS firms are similar in terms of sales growth, suggesting the effectiveness of our matching process. Due to the multinational business nature of CL IFRS firms, it is unsurprising that CL IFRS firms are much larger than NCL IFRS firms. Moreover, CL IFRS firms have lower asset turnover, indicating that they are more capital-intensive than NCL IFRS firms. Book-to-market ratio is significantly lower for CL IFRS firms than for NCL IFRS firms, which reflects the difference in growth opportunities between CL IFRS and NCL IFRS firms. As to the rest of the control variables, on average, CL IFRS firms have a smaller magnitude of changes in cashbasis sales, issue less equity, and report losses less frequently than NCL IFRS firms. 5. Empirical findings 5.1. Main results Table 4 presents the findings for our main tests. Using NCL IFRS firms as the control sample, our analyses focus on whether the changes in accounting attributes between the pre- and post-elimination periods for CL IFRS firms are incremental to those for NCL IFRS firms. This research design helps to control for the contemporaneous evolution of IFRS and changes in the local macro-environment, mitigating the concern that our results are confounded by factors other than the regulatory change. Panel A of Table 4 reports results from the regression analysis of accounting discretion contained in reported earnings, as proxied by absolute discretionary working capital accruals. The coefficient on POST × CL is significantly negative while the coefficient on CL is statistically positive, indicating that CL IFRS firms exercise more discretion over accounting

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Table 2 Frequencies of cross-listed IFRS firms. Number of CL IFRS firm-years Panel A: Location of headquarters Australia 34 Belgium 4 China 32 Denmark 8 Finland 4 France 28 Germany 15 Hungary 4 Ireland 16 Italy 8 Luxembourg 12 Mexico 4 Netherlands 31 New Zealand 4 Papua New Guinea 4 Portugal 4 Russia 4 South Africa 10 Spain 8 Sweden 4 Switzerland 12 Turkey 3 United Kingdom 77 _ Total 330 Panel B: Industry sectors (GICS) Energy 55 Materials 48 Industrials 26 Consumer discretionary 40 Consumer staples 20 Health care 44 Financials 24 Information technology 16 Telecommunication services 57 Total 330

_

Percentage of CL IFRS firm-years 10.30 1.21 9.70 2.42 1.21 8.48 4.55 1.21 4.85 2.42 3.64 1.21 9.39 1.21 1.21 1.21 1.21 3.03 2.42 1.21 3.64 0.91 23.33

Number of unique CL IFRS firms

Percentage of unique CL IFRS firms

100.00

_

9 1 8 2 1 7 4 1 4 2 3 1 9 1 1 1 1 3 2 1 3 1 20 _ 86

_

100.00

16.67 14.55 7.88 12.12 6.06 13.33 7.27 4.85 17.27 100.00

14 12 7 11 5 12 6 4 15 86

16.28 13.95 8.14 12.79 5.81 13.95 6.98 4.65 17.44 100.00

_

10.47 1.16 9.30 2.33 1.16 8.14 4.65 1.16 4.65 2.33 3.49 1.16 10.47 1.16 1.16 1.16 1.16 3.49 2.33 1.16 3.49 1.16 23.26

_

_

choices than NCL IFRS firms in the pre-elimination period but appear to lessen the use of accounting discretion after the 20-F reconciliation is eliminated. This finding demonstrates how the change in the reconciliation requirement affects firms' reporting incentives, as reflected in the extent to which managers exercise accounting discretion granted by IFRS. The significantly negative coefficient on POST + POST × CL reveals that CL IFRS firms have a smaller amount of discretionary working capital accruals after the rule change,

Table 3 Descriptive statistics. Cross-listed IFRS firms Mean

Median

Std dev

Q1

163 242 242

0.03 0.03 0.07

0.02 0.05 0.05

0.05 0.12 0.49

0.00 0.03 − 0.28

163 163 163 163 163 163 163 163 163 242 242

0.11 0.04 9.11 0.04 0.48 1.81 0.68 0.10 0.19 0.44 0.14

0.07 0.06 9.40 0.01 0.06 1.03 0.62 0.11 0.09 0.35 0.00

0.10 0.20 2.42 0.28 3.10 4.90 0.40 0.16 0.61 0.36 0.35

0.03 0.02 7.95 − 0.06 − 0.11 0.53 0.41 0.06 − 0.04 0.19 0.00

Q3

N

Mean

Median

Std dev

Q1

Q3

0.03 0.08 0.35

170 238 238

0.04 ⁎⁎ − 0.02 ⁎⁎⁎ − 0.03 ⁎⁎

0.02 ⁎⁎⁎ 0.04 ⁎⁎⁎ − 0.06 ⁎⁎

0.06 0.19 0.51

0.01 − 0.04 − 0.40

0.06 0.07 0.30

0.15 0.12 11.19 0.11 0.25 1.85 0.86 0.19 0.22 0.62 0.00

170 170 170 170 170 170 170 170 170 238 238

0.17 ⁎⁎⁎ 0.01 5.93 ⁎⁎⁎ 0.37 ⁎⁎ 1.16 1.98 1.00 ⁎⁎⁎ 0.07 ⁎⁎ 0.12 0.80 ⁎⁎⁎ 0.29 ⁎⁎⁎

0.11 ⁎⁎⁎ 0.04 ⁎⁎⁎ 5.95 ⁎⁎⁎ 0.07 ⁎⁎⁎ 0.06 1.15 0.93 ⁎⁎⁎ 0.09 ⁎⁎⁎ 0.09 0.58 ⁎⁎⁎ 0.00 ⁎⁎⁎

0.17 0.15 2.01 1.78 5.64 4.23 0.72 0.13 0.55 0.72 0.45

0.04 0.00 4.68 − 0.05 − 0.20 0.73 0.43 0.03 − 0.07 0.37 0.00

0.25 0.08 7.23 0.13 0.39 1.84 1.42 0.13 0.24 1.05 1.00

a

Control variables b ABS(ΔSALES − ΔAR) ROA SIZE EISSUE DISSUE LEV TURN CF GROWTH BM LOSS

⁎ Significantly different between CL IFRS firms and NCL IFRS firms at the 0.10 level (two-tailed). ⁎⁎ Significantly different between CL IFRS firms and NCL IFRS firms at the 0.05 level (two-tailed). ⁎⁎⁎ Significantly different between CL IFRS firms and NCL IFRS firms at the 0.01 level (two-tailed). a We define ABSWCACC as the absolute value of working capital accruals, which are computed as (increase in accounts receivable + increase in inventory + decrease in accounts payable + decrease in income tax payable + net change in other accrued liabilities) / lagged total assets; E as earnings per share excluding extraordinary items scaled by price at the beginning of the year; and R as the 15-month buy-and-hold return for the period ending three months after the fiscal year-end. b We define ABS(ΔSALES − ΔAR) as the absolute value of the change in sales net of the change in accounts receivables, scaled by lagged total assets; ROA as net income divided by lagged total assets; SIZE as the natural logarithm of year-end market value of equity in millions; EISSUE as the percentage change in common stock; DISSUE as the percentage change in debt; LEV as year-end total liabilities divided by year-end total equity; TURN as sales divided by total assets; CF as annual net cash flow from operating activities scaled by lagged total assets; GROWTH as the percentage change in sales; BM as the book value of equity scaled by the market value of equity; and LOSS as an indicator variable taking the value of one if earnings before extraordinary items are negative, and zero otherwise.

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Test variables ABSWCACC E R

Non-cross-listed IFRS firms

N

67

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suggesting that CL IFRS firms' reported earnings contain less accounting discretion in the post-elimination period than in the pre-elimination period. The coefficient on POST is insignificantly different from zero, showing that there is no significant change in the magnitude of discretionary working capital accruals from the pre- to the post-elimination period for NCL IFRS firms. Taken together, these results provide evidence that CL IFRS firms' difference-minimizing incentives are mitigated by the removal of the U.S. GAAP reconciliation, leading to less accounting discretion being exercised over IFRS-based earnings. Results for the degree of asymmetric timely loss recognition are reported in Panel B of Table 4. 19 The insignificant coefficient on POST × R × DUM for NCL IFRS firms shows that NCL IFRS firms recognize gains and losses in a similar manner during the entire sample period. However, the coefficient on POST × R × DUM is significantly positive for CL IFRS firms, indicating that relative to the pre-elimination period, CL IFRS firms incorporate losses into earnings in a timelier fashion than gains in the post-elimination period. Panel C of Table 4 presents results for the value relevance test. We find that the return– earnings relation for CL IFRS firms is worse than that for NCL IFRS firms in the preelimination period, as evidenced by the statistically negative coefficient on E × CL. This result implies that the informativeness of earnings is sacrificed when CL IFRS firms bias their accounting methods toward those minimizing the U.S. GAAP reconciliation. 20 The significantly positive coefficient on E × POST × CL, however, reveals that the value relevance of accounting information for CL IFRS firms is considerably enhanced after the regulatory change. This suggests that accounting choices made by CL IFRS firms after the elimination of the reconciliation requirement better capture the changes in the firm's underlying economics, thereby enhancing earnings informativeness. Further, the coefficient on E × POST + E × POST × CL is significantly positive, which reflects the improvement in the association between returns and earnings from the pre- to the post-elimination period for CL IFRS firms. In contrast, the insignificant coefficient on E × POST shows that NCL IFRS firms do not experience such improvement in the return–earnings relation. In summary, we find that CL IFRS firms' reported earnings exhibit differences in the amount of accounting discretion, asymmetric timeliness, and value relevance between the pre- and post-elimination periods. These changes in the quality of IFRS-based numbers reflect how the reconciliation requirement affects the application of IFRS by CL IFRS firms. When CL IFRS firms are not required to provide the U.S. GAAP reconciliation, they can choose more appropriate accounting methods within IFRS without the concern of disclosing

Previous studies have shown that firm size, market-to-book ratio, leverage, and litigation risk are associated with the asymmetric timeliness of earnings (e.g., Lafond & Roychowdhury, 2008; LaFond & Watts, 2008). Our results are generally the same after controlling for these factors. 20 It is possible that CL IFRS firms communicate value-relevant information through other channels to compensate for less informative accounting earnings in the pre-elimination period, thereby avoiding valuation losses. We thank the reviewer for pointing out this possibility. 19

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Table 4 Comparison of cross-listed IFRS and non-cross-listed IFRS firms' accounting characteristics before and after the elimination of the reconciliation requirement. Measure a Panel A: Accounting discretion contained in reported earnings b ABSWCACC it ¼ α 0 þ α 1 POST it þ α 2 CLit þ α 3 POST it  CLit þ α 4 ABSðΔSALESit −ΔARit Þ þ α 5 ROAit þ α 6 SIZEit þ α 7 EISSUEit þ α 8 DISSUEit þ α 9 LEV it þ α 10 TURNit þ α 11 CFit þα 12 GROWTHit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable

Coefficient

t-statistic

Intercept POST CL POST × CL ABS(ΔSALES − ΔAR) ROA SIZE EISSUE DISSUE LEV TURN CF GROWTH Year dummies Country dummies Industry dummies Test for α1 + α3 = 0: N Adjusted R2

0.074 ⁎⁎⁎ 0.001 0.017 ⁎⁎ − 0.017 ⁎⁎⁎ 0.079 ⁎ − 0.100 ⁎⁎⁎ − 0.005 ⁎⁎ 0.007 0.001 ⁎⁎ − 0.001 ⁎⁎ 0.008 0.042 ⁎ 0.012

3.26 0.13 2.33 − 3.52 1.73 − 2.80 − 2.26 1.26 2.08 − 2.03 0.94 1.69 1.53 Yes Yes Yes

p-Value = 0.00 ⁎⁎⁎

333 0.35

Panel B: Asymmetric timely loss recognition c Eit ¼ α 0 þ α 1 Rit þ α 2 DUMit þ α 3 Rit  DUMit þ α 4 POST it þ α 5 POST it  Rit þ α 6 POST it  DUMit þα 7 POST it  Rit  DUMit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable CL IFRS firms Intercept R DUM R × DUM POST POST × R POST × DUM POST × R × DUM Year dummies Country dummies Industry dummies Test for α3 + α7 = 0: N Adjusted R2

Coefficient

t-statistic

0.054 − 0.086 − 0.055 ⁎ − 0.061 − 0.029 0.087 0.139 ⁎⁎ 0.387 ⁎⁎

0.87 − 1.59 − 1.96 − 0.43 − 1.62 1.44 2.25 2.24 Yes Yes Yes

p-Value = 0.00 ⁎⁎

242 0.34 (continued on next page)

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Table 4 (continued) Panel B: Asymmetric timely loss recognition c Eit ¼ α 0 þ α 1 Rit þ α 2 DUMit þ α 3 Rit  DUMit þ α 4 POST it þ α 5 POST it  Rit þ α 6 POST it  DUMit þα 7 POST it  Rit  DUMit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable NCL IFRS firms Intercept R DUM R × DUM POST POST × R POST × DUM POST × R × DUM Year dummies Country dummies Industry dummies Test for α3 + α7 = 0: N Adjusted R2

Coefficient

t-statistic

0.112 − 0.006 − 0.004 0.160 ⁎⁎⁎ − 0.025 − 0.150 ⁎ − 0.017 0.104

1.29 − 0.22 − 0.05 3.09 − 0.50 − 1.89 − 0.36 0.81 Yes Yes Yes

p-Value = 0.09 ⁎

238 0.15

Panel C: Value relevance of accounting numbers d Rit ¼ α 0 þ α 1 Eit þ α 2 POST it þ α 3 Eit  POST it þ α 4 CLit þ α 5 Eit  CLit þ α 6 POST it  CLit þ α 7 Eit  POST it  CLit þ α 8 SIZEit þ α 9 Eit  SIZEit þ α 10 BMit þ α 11 Eit  BMit þ α 12 LOSSit þα 13 Eit  LOSSit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable

Coefficient

t-statistic

Intercept E POST E × POST CL E × CL POST × CL E × POST × CL SIZE E × SIZE BM E × BM LOSS E × LOSS Year dummies Country dummies Industry dummies Test for α3 + α7 = 0: N Adjusted R2

0.402 ⁎ 1.606 − 0.568 ⁎⁎⁎ − 0.209 0.060 − 1.647 ⁎ − 0.053 1.877 ⁎⁎⁎ − 0.006 0.066 − 0.172 ⁎⁎⁎ − 0.197 − 0.140 − 1.642

1.78 1.43 − 5.99 − 0.60 0.58 − 1.78 − 0.34 3.01 − 0.42 0.71 − 4.56 − 1.03 − 1.04 − 1.53 Yes Yes Yes

p-Value = 0.00 ⁎⁎⁎

480 0.48

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large reconciliation differences in 20-Fs. It implies that the SEC's previous reconciliation requirement may have unintended consequences on CL IFRS firms' reporting incentives, leading to lower quality IFRS-based accounting data. Since NCL IFRS firms do not display the same changes in accounting characteristics as CL IFRS firms, it is unlikely that our results are attributed to factors beyond the regulatory change of interest. 5.2. Supplementary analyses 5.2.1. Cross-sectional variation: split on public enforcement An important motivation behind firms' incentives to minimize the reconciliation is that large reconciliation differences revealed in 20-F filings would likely trigger scrutiny from local authorities (Leuz, 2006). To avoid costs resulting from regulatory investigation, managers tend to reduce the materiality of the reconciliation through choosing accounting policies closer to U.S. GAAP. This behavior is consistent with the earnings management literature that regulatory scrutiny induces firms to manage earnings (see Healy & Wahlen, 1999). The more intense the local monitoring, the greater is the likelihood that regulators will question the large reconciliation differences. As a result, firms subject to more intense local monitoring are more likely to exercise discretion over accounting choices to minimize the reconciliation. We thus expect that the impact of eliminating the reconciliation requirement on the changes in the quality of IFRS-based accounting information is more pronounced for CL IFRS firms with stronger local monitoring. Our analysis across different degrees of local monitoring is primarily based on the public enforcement index created by La Porta et al. (2006), which is a summary index of supervisor characteristics index, rule-making power index, investigative powers index, orders index, and criminal index and ranges from zero to one. We assign firms from countries that score

Notes to Table 4: ⁎ Significantly different from zero at the 0.10 level (two-tailed). ⁎⁎ Significantly different from zero at the 0.05 level (two-tailed). ⁎⁎⁎ Significantly different from zero at the 0.01 level (two-tailed). a The number of observations varies slightly across models because of the additional variables required in different models. For parsimony, the coefficients on year, country, and industry dummies are suppressed. We winsorize all continuous variables at the 1% level to control for outliers. Standard errors are calculated based on Petersen's (2009) double cluster procedure to allow inter-correlations of residuals across firms or across time. b ABSWCACC is the absolute value of working capital accruals, which are computed as (increase in accounts receivable + increase in inventory + decrease in accounts payable + decrease in income tax payable + net change in other accrued liabilities) / lagged total assets, POST is an indicator variable set equal to one if firm-year observations are from the post-elimination period and zero otherwise, CL is an indicator variable that equals one for CL IFRS firm-year observations and zero for NCL IFRS ones, and control variables are as defined in Table 3. c The regression is estimated separately for CL IFRS and NCL IFRS firms, where E is earnings per share excluding extraordinary items scaled by price at the beginning of the year, R is the 15-month buy-and-hold return for the period ending three months after the fiscal year-end, and DUM is an indicator variable taking the value of one if the return is negative and zero otherwise. d R, E, POST, and CL are as defined above, and control variables are as defined in Table 3.

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above (below) 0.5 to the high (low) public enforcement sample. 21 High public enforcement countries in our sample are Australia, France, Portugal, Turkey, and the United Kingdom; low public enforcement countries are Belgium, China, Denmark, Finland, Germany, Hungary, Ireland, Italy, Luxembourg, Mexico, Netherlands, New Zealand, Papua New Guinea, Russia, South Africa, Spain, Sweden, and Switzerland. Results for the high/low public enforcement split are presented in Table 5. In Panel A of Table 5, the difference in the coefficient on POST × CL between high and low public enforcement samples is negative (− 0.024) and significant at the 1% level (two-tailed) and the difference in the coefficient on E × POST × CL between the two samples in Panel C of Table 5 is positive (0.592) and significant at the 10% level (one-tailed). Overall, the decrease in accounting discretion and the increase in the value relevance of reported earnings between the pre- and the post-elimination periods that we document in the primary analysis are driven by CL IFRS firms domiciled in countries with high enforcement. 22 These results suggest that the materiality of the reconciliation may be a more serious concern for CL IFRS firms subject to a higher degree of local monitoring so that they have more incentives to minimize the reconciliation to lower the expected costs related to regulatory scrutiny. Consequently, the removal of the U.S. GAAP reconciliation has a greater effect on CL IFRS firms from high enforcement countries, as reflected in the changes in the quality of accounting data resulting from the application of IFRS. 5.2.2. Years covered by the sample period To see whether our findings are driven by a specific year in the sample period, we drop one year at a time and use the remaining three years' data to re-estimate Eqs. (1)–(3). That is, we rerun regressions (1)–(3) separately for the period covering (1) fiscal years 2007, 2008, and 2009, (2) fiscal years 2006, 2008, and 2009, (3) fiscal years 2006, 2007, and 2009, and (4) fiscal years 2006, 2007, and 2008. Our results are robust to this sensitivity check. 5.2.3. Analysis of working capital accruals: components and sign We decompose working capital accruals into the current asset component and the current liability component to assess whether specific working capital components drive our results for the accrual test. For this purpose, we rerun regression (1) replacing absolute working capital accruals with the components of current assets and current liabilities. The finding of the decline in the magnitude of discretionary working capital accruals from the pre- to the post-elimination period is primarily due to the decrease in the current asset component. Moreover, we re-estimate Eq. (1) separately for positive and negative working capital accruals. We find similar but less significant pre- and post-changes in the magnitude of discretionary working capital accruals for both positive and negative groups. It is likely that managers exercise discretion over both income-increasing and income-decreasing accruals 21

There are some countries for which ratings are not available in La Porta et al. (2006). We classify China, Hungary, Luxembourg, Papua New Guinea, and Russia as low public enforcement countries. Results are not sensitive to the inclusion of these observations. 22 The finding that the increase in the value relevance of reported earnings between the pre- and the postelimination periods is driven by firms from high enforcement countries holds for both positive and negative earnings.

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Table 5 Comparison of cross-listed IFRS and non-cross-listed IFRS firms' accounting characteristics before and after the elimination of the reconciliation requirement: split on public enforcement. a Measure b Panel A: Accounting discretion contained in reported earnings c ABSWCACC it ¼ γ0 þ γ1 POST it þ γ 2 CLit þ γ3 POST it  CLit þ γ 4 ABSðΔSALESit −ΔARit Þ þ γ 5 ROAit þ γ6 SIZEit þ γ 7 EISSUEit þ γ 8 DISSUEit þ γ 9 LEV it þ γ 10 TURNit þ γ 11 CFit þγ 12 GROWTHit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable High public enforcement Intercept POST CL POST × CL ABS(ΔSALES − ΔAR) ROA SIZE EISSUE DISSUE LEV TURN CF GROWTH Year dummies Country dummies Industry dummies Test for γ1 + γ3 = 0: N Adjusted R2 Low public enforcement Intercept POST CL POST × CL ABS(ΔSALES − ΔAR) ROA SIZE EISSUE DISSUE LEV TURN CF GROWTH Year dummies Country dummies Industry dummies Test for γ1 + γ3 = 0: N Adjusted R2

Coefficient

t-statistic

0.081 ⁎⁎⁎ 0.013 0.047 ⁎⁎⁎ − 0.027 ⁎⁎⁎ 0.120 ⁎⁎ − 0.133 ⁎⁎⁎ − 0.008 ⁎⁎ 0.005 0.002 ⁎⁎⁎ − 0.001 ⁎⁎⁎ 0.008 0.111 ⁎⁎⁎ 0.008 ⁎⁎⁎

4.01 1.00 4.55 − 5.79 2.17 − 3.55 − 2.48 1.13 3.20 − 2.79 0.58 7.16 4.62 Yes Yes Yes

p-Value = 0.14 161 0.49

− 0.003 0.015 − 0.007 − 0.003 0.004 0.055 − 0.002 0.005 ⁎ 0.000 − 0.002 ⁎⁎⁎ 0.005 − 0.147 0.021

p-Value = 0.00 ⁎⁎⁎

− 0.11 1.66 − 0.60 − 1.18 0.20 0.62 − 0.86 1.73 0.70 − 3.20 0.62 − 1.35 1.12 Yes Yes Yes 172 0.37 (continued on next page)

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Table 5 (continued) Panel B: Asymmetric timely loss recognition d Eit ¼ γ 0 þ γ 1 Rit þ γ 2 DUMit þ γ 3 Rit  DUMit þ γ4 POST it þ γ 5 POST it  Rit þ γ 6 POST it  DUMit þγ7 POST it  Rit  DUMit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable

High public enforcement Intercept R DUM R × DUM POST POST × R POST × DUM POST × R × DUM Year dummies Country dummies Industry dummies Test for γ3 + γ7 = 0: N Adjusted R2 Low public enforcement Intercept R DUM R × DUM POST POST × R POST × DUM POST × R × DUM Year dummies Country dummies

CL IFRS firms

NCL IFRS firms

Coefficient (t-statistic)

Coefficient (t-statistic)

0.028 (0.36) − 0.135 (− 1.48) − 0.037 (− 0.57) 0.131 (0.56) − 0.024 (− 0.80) 0.031 (0.43) 0.106 ⁎ (1.71) 0.259 (1.06) Yes Yes Yes p-Value = 0.00 ⁎⁎⁎ 127 0.39

0.073 (0.55) − 0.011 (− 0.27) − 0.056 (− 0.96) 0.139 (1.33) − 0.055 (− 0.71) − 0.155 (− 0.41) − 0.029 (− 0.71) 0.078 (0.19) Yes Yes Yes p-Value = 0.41 126 0.16

0.171 ⁎⁎⁎ (3.44) − 0.036 (− 0.93) − 0.020 (− 0.60) − 0.091 (− 0.56) 0.018 (0.87) 0.056 (1.01) 0.101 (1.39) 0.433 ⁎ (1.80) Yes Yes

0.214 ⁎ (1.68) 0.019 (0.32) − 0.058 (− 0.41) − 0.827 (− 1.15) 0.064 (1.11) − 0.036 (− 0.26) 0.105 (1.00) 1.119 ⁎ (1.87) Yes Yes

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Table 5 (continued) Panel B: Asymmetric timely loss recognition d Eit ¼ γ 0 þ γ 1 Rit þ γ 2 DUMit þ γ 3 Rit  DUMit þ γ4 POST it þ γ 5 POST it  Rit þ γ 6 POST it  DUMit þγ7 POST it  Rit  DUMit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable

Low public enforcement Industry dummies Test for γ3 + γ7 = 0: N Adjusted R2

CL IFRS firms

NCL IFRS firms

Coefficient (t-statistic)

Coefficient (t-statistic)

Yes p-Value = 0.05 ⁎ 115 0.25

Yes p-Value = 0.20 112 0.14

Panel C: Value relevance of accounting numbers e Rit ¼ γ0 þ γ1 Eit þ γ 2 POST it þ γ3 Eit  POST it þ γ 4 CLit þ γ5 Eit  CLit þ γ6 POST it  CLit þ γ 7 Eit  POST it  CLit þ γ8 SIZEit þ γ9 Eit  SIZEit þ γ10 BMit þ γ 11 Eit  BMit þ γ12 LOSSit þγ13 Eit  LOSSit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable High public enforcement Intercept E POST E × POST CL E × CL POST × CL E × POST × CL SIZE E × SIZE BM E × BM LOSS E × LOSS Year dummies Country dummies Industry dummies Test for γ3 + γ7 = 0: N Adjusted R2 Low public enforcement Intercept E POST E × POST CL E × CL POST × CL E × POST × CL SIZE

Coefficient

t-statistic

0.068 3.439 ⁎⁎ − 0.314 ⁎⁎⁎ − 0.208 0.081 − 1.984 ⁎ − 0.139 2.249 ⁎⁎⁎ 0.006 0.020 − 0.138 ⁎⁎⁎ 0.114 0.024 − 3.382 ⁎⁎

0.21 2.15 − 3.23 − 0.47 0.72 − 1.84 − 0.69 3.51 0.27 0.16 − 4.11 0.57 0.24 − 2.10 Yes Yes Yes

p-Value = 0.00 ⁎⁎⁎

253 0.43 0.842 ⁎⁎⁎ − 0.030 − 0.454 ⁎⁎⁎ − 0.023 0.130 − 1.484 ⁎⁎⁎ 0.068 1.657 ⁎⁎⁎ − 0.063 ⁎⁎⁎

3.87 − 0.06 − 5.46 − 0.06 0.71 − 8.30 0.41 3.27 − 3.86 (continued on next page)

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Table 5 (continued) Panel C: Value relevance of accounting numbers e Rit ¼ γ0 þ γ1 Eit þ γ 2 POST it þ γ3 Eit  POST it þ γ 4 CLit þ γ5 Eit  CLit þ γ6 POST it  CLit þ γ 7 Eit  POST it  CLit þ γ 8 SIZEit þ γ9 Eit  SIZEit þ γ10 BMit þ γ 11 Eit  BMit þ γ 12 LOSSit þγ13 Eit  LOSSit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable

Coefficient

t-statistic

E × SIZE BM Low public enforcement E × BM LOSS E × LOSS Year dummies Country dummies Industry dummies Test for γ3 + γ7 = 0: N Adjusted R2

0.193 ⁎⁎⁎ − 0.195 ⁎⁎⁎

3.03 − 15.37

− 0.250 ⁎⁎ − 0.324 − 0.753

− 2.36 − 1.51 − 0.97 Yes Yes Yes

p-Value = 0.00 ⁎⁎⁎

227 0.57

⁎ Significantly different from zero at the 0.10 level (two-tailed). ⁎⁎ Significantly different from zero at the 0.05 level (two-tailed). ⁎⁎⁎ Significantly different from zero at the 0.01 level (two-tailed). a The classification for high and low public enforcement is based on the public enforcement index created by La Porta et al. (2006). High public enforcement subsample is composed of firms from Australia, France, Portugal, Turkey, and the United Kingdom; low public enforcement subsample comprises firms from Belgium, China, Denmark, Finland, Germany, Hungary, Ireland, Italy, Luxembourg, Mexico, Netherlands, New Zealand, Papua New Guinea, Russia, South Africa, Spain, Sweden, and Switzerland. b The number of observations varies slightly across models because of the additional variables required in different models. For parsimony, the coefficients on year, country, and industry dummies are suppressed. We winsorize all continuous variables at the 1% level to control for outliers. Standard errors are calculated based on Petersen's (2009) double cluster procedure to allow inter-correlations of residuals across firms or across time. c ABSWCACC is the absolute value of working capital accruals, which are computed as (increase in accounts receivable + increase in inventory + decrease in accounts payable + decrease in income tax payable + net change in other accrued liabilities) / lagged total assets, POST is an indicator variable set equal to one if firm-year observations are from the post-elimination period and zero otherwise, CL is an indicator variable that equals one for CL IFRS firm-year observations and zero for NCL IFRS ones, and control variables are as defined in Table 3. d The regression is estimated separately for CL IFRS and NCL IFRS firms across high and low levels of public enforcement, where E is earnings per share excluding extraordinary items scaled by price at the beginning of the year, R is the 15-month buy-and-hold return for the period ending three months after the fiscal year-end, and DUM is an indicator variable taking the value of one if the return is negative and zero otherwise. e R, E, POST, and CL are as defined above, and control variables are as defined in Table 3.

to achieve the desired outcome. As a result, statistical significance decreases when these two types of accruals are examined separately. 5.2.4. Using U.S. firms as the control sample Since CL IFRS firms are traded on both the U.S. and local exchanges, contemporaneous changes in the U.S. markets may also have an effect on these firms' accounting attributes. To rule out the possibility that our findings are driven by the changes in the U.S. macroenvironment as opposed to the regulatory change of interest, we rerun regressions (1)–(3)

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Table 6 Comparison of cross-listed IFRS and U.S. firms' accounting characteristics in the pre- and post-elimination periods. Measure a Panel A: Accounting discretion contained in reported earnings b ABSWCACC it ¼ β0 þ β1 POST it þ β2 IFRSit þ β3 POST it  IFRSit þ β4 ABSðΔSALESit −ΔARit Þ þ β5 ROAit þ β6 SIZEit þ β7 EISSUEit þ β8 DISSUEit þ β9 LEV it þ β10 TURNit þ β11 CFit þβ12 GROWTHit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable

Coefficient

t-statistic

Intercept POST IFRS POST × IFRS ABS(ΔSALES − ΔAR) ROA SIZE EISSUE DISSUE LEV TURN CF GROWTH Year dummies Country dummies Industry dummies Test for β2 + β3 = 0: N Adjusted R2

0.044 − 0.004 0.044 ⁎⁎ − 0.016 0.106 ⁎ − 0.132 ⁎⁎⁎ − 0.007 ⁎⁎ 0.003 0.003 − 0.001 ⁎⁎ 0.002 0.123 ⁎⁎⁎ 0.061 ⁎⁎⁎

1.19 − 0.50 1.99 − 1.37 1.88 − 3.45 − 2.44 0.44 0.43 − 2.52 0.37 4.27 5.14 Yes Yes Yes

p-Value = 0.40 388 0.54

Panel B: Asymmetric timely loss recognition c Eit ¼ β0 þ β1 Rit þ β2 DUMit þ β3 Rit  DUMit þ β4 IFRSit þ β5 IFRSit  Rit þ β6 IFRSit  DUMit þβ7 IFRSit  Rit  DUMit þ Year dummies þ Country dummies þ Industry dummies þ ε it Variable Pre-elimination period Intercept R DUM R × DUM IFRS IFRS × R IFRS × DUM IFRS × R × DUM Year dummies Country dummies Industry dummies Test for β3 + β7 = 0: N Adjusted R2 Post-elimination period

Coefficient

t-statistic

0.104 ⁎⁎⁎ 0.026 0.001 0.152 ⁎ 0.089 ⁎ − 0.069 ⁎ − 0.027 0.026

9.25 1.18 0.02 1.93 1.97 − 1.94 − 0.30 0.09 Yes Yes Yes

p-Value = 0.39 219 0.20 (continued on next page)

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Table 6 (continued) Panel B: Asymmetric timely loss recognition c Eit ¼ β0 þ β1 Rit þ β2 DUMit þ β3 Rit  DUMit þ β4 IFRSit þ β5 IFRSit  Rit þ β6 IFRSit  DUMit þβ7 IFRSit  Rit  DUMit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable Intercept R DUM R × DUM IFRS IFRS × R IFRS × DUM IFRS × R × DUM Year dummies Country dummies Industry dummies Test for β3 + β7 = 0: N Adjusted R2

Coefficient

t-statistic

0.103 ⁎⁎⁎ 0.048 0.164 0.466 ⁎⁎⁎ − 0.060 − 0.049 ⁎⁎ − 0.106 ⁎⁎ − 0.275

3.16 0.63 1.52 3.68 − 0.96 − 2.54 − 2.34 − 1.65 Yes Yes Yes

p-Value = 0.00 ⁎⁎⁎

223 0.24

Panel C: Value relevance of accounting numbers d Rit ¼ β0 þ β1 Eit þ β2 POST it þ β3 Eit  POST it þ β4 IFRSit þ β5 Eit  IFRSit þ β6 POST it  IFRSit þ β7 Eit  POST it  IFRSit þ β8 SIZEit þ β9 Eit  SIZEit þ β10 BMit þ β11 Eit  BMit þ β12 LOSSit þβ13 Eit  LOSSit þ Year dummies þ Country dummies þ Industry dummies þ εit Variable

Coefficient

t-statistic

Intercept E POST E × POST IFRS E × IFRS POST × IFRS E × POST × IFRS SIZE E × SIZE BM E × BM LOSS E × LOSS Year dummies Country dummies Industry dummies Test for β5 + β7 = 0: N Adjusted R2

0.118 2.803 ⁎⁎⁎ − 0.238 ⁎⁎⁎ − 0.006 0.060 − 0.938 ⁎⁎⁎ − 0.150 1.076 ⁎⁎⁎ 0.005 0.005 − 0.237 ⁎⁎ − 0.416 ⁎⁎⁎ − 0.116 − 2.506 ⁎⁎⁎

0.39 4.21 − 3.69 − 0.02 0.21 − 3.89 − 0.98 2.81 0.42 0.18 − 2.16 − 2.74 − 1.53 − 4.58 Yes Yes Yes

p-Value = 0.56 442 0.49

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using U.S. firms as the control sample. Results for the accrual test and the value relevance test are robust to the use of this alternative U.S. control sample but the asymmetric timely loss recognition test exhibits slightly different results. We find no significant change in the asymmetric timeliness of earnings between the pre- and post-elimination periods for CL IFRS firms.

6. Accounting quality under IFRS and U.S. GAAP The SEC has recently been deliberating the potential use of financial statements prepared in accordance with IFRS by U.S. issuers. One critical consideration underlying the SEC's deliberation is whether accounting numbers resulting from the application of IFRS are of higher or lower quality than those resulting from the application of U.S. GAAP. Leuz (2003) finds insignificant differences in information asymmetry and market liquidity between firms applying U.S. GAAP and those applying IAS in the German New Market. Similarly, Bartov et al. (2005) report higher value relevance of earnings for German firms reporting under either U.S. GAAP or IAS than for those reporting under German GAAP, but they do not find a significant difference in value relevance between U.S. GAAP- and IAS-based earnings. Neither study supports the claim that U.S. GAAP is superior to IAS. In contrast, Barth et al. (2010) provide evidence that accounting numbers are generally more value relevant for U.S. firms applying U.S. GAAP than for non-U.S. firms applying IAS. Goncharov and Zimmermann (2006) and Van der Meulen, Gaeremynck, and Willekens (2007) also show that German firms adopting U.S. GAAP provide better accounting information than those adopting IAS, suggesting that U.S. GAAP-based numbers are of higher quality than IAS-based numbers.

Notes to Table 6: ⁎ Significantly different from zero at the 0.10 level (two-tailed). ⁎⁎ Significantly different from zero at the 0.05 level (two-tailed). ⁎⁎⁎ Significantly different from zero at the 0.01 level (two-tailed). a The number of observations varies slightly across models because of the additional variables required in different models. For parsimony, the coefficients on year, country, and industry dummies are suppressed. We winsorize all continuous variables at the 1% level to control for outliers. Standard errors are calculated based on Petersen's (2009) double cluster procedure to allow inter-correlations of residuals across firms or across time. b ABSWCACC is the absolute value of working capital accruals, which are computed as (increase in accounts receivable + increase in inventory + decrease in accounts payable + decrease in income tax payable + net change in other accrued liabilities) / lagged total assets, POST is an indicator variable set equal to one if firm-year observations are from the post-elimination period and zero otherwise, IFRS is an indicator variable that equals one for CL IFRS firm-year observations and zero for U.S. ones, and control variables are as defined in Table 3. c The regression is estimated separately for the pre- and post-elimination periods, where E is earnings per share excluding extraordinary items scaled by price at the beginning of the year, R is the 15-month buy-and-hold return for the period ending three months after the fiscal year-end, and DUM is an indicator variable taking the value of one if the return is negative and zero otherwise. d R, E, POST, and IFRS are as defined above, and control variables are as defined in Table 3.

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Most of the studies on the comparison of accounting quality under IFRS/IAS and U.S. GAAP either are based on firms from a wide range of IFRS-adopting countries or are in the context of Germany. 23 Considerable institutional differences exist between U.S. and other major equity markets; therefore, we cannot generalize to U.S. publicly traded companies from the conclusions based on prior research. In terms of investor clientele and product market interactions, firms cross-listed in the U.S. tend to be more similar to U.S. firms. Furthermore, cross-listed firms are subject to SEC regulation and U.S. security laws as are U.S. firms. Hence, employing CL IFRS firms to compare accounting quality resulting from applying IFRS with that resulting from applying U.S. GAAP can provide the most relevant evidence for the debate over whether U.S. firms should adopt IFRS. Using cross-listed firms that filed 20-F reconciliations from IFRS to U.S. GAAP between 2004 and 2006, Gordon et al. (2008) document that earnings quality under IFRS is comparable with that under U.S. GAAP, with the exception that U.S. GAAP-based numbers exhibit higher value relevance than IFRS-based numbers. Note that the sample period examined in Gordon et al. (2008) is before the elimination of the U.S. GAAP reconciliation. As discussed earlier, the reconciliation requirement may influence the application of IFRS by CL IFRS firms; the quality of IFRS-based numbers is affected accordingly. Therefore, it is worth re-examining accounting quality under IFRS and U.S. GAAP using the period after the reconciliation requirement is removed. Panel B of Fig. 1 illustrates this additional analysis. We do not make a directional prediction as to which set of accounting standards produces superior information because the extant literature is inconclusive on this front. On the other hand, U.S. GAAP and IFRS have evolved substantially in recent years partly due to the convergence efforts made by the FASB and IASB, which might reduce the differences in accounting quality between U.S. GAAP and IFRS. To compare the magnitude of managerial discretion over accounting numbers between CL IFRS and U.S. firms, we estimate the following regression model pooling all CL IFRS and U.S. sample firm-years:

ABSWCACC it ¼ β 0 þ β1 POST it þ β2 IFRSit þ β3 POST it  IFRSit þ β4 ABSðΔSALESit −ΔARit Þ þ β 5 ROAit þ β 6 SIZEit þ β7 EISSUEit þ β8 DISSUEit þ β9 LEV it þ β10 TURN it þβ 11 CFit þ β12 GROWTH it þ Year dummies þ Country dummies þIndustry dummies þ εit

ð4Þ

23 German companies are allowed to choose among IAS/IFRS, U.S. GAAP, and German GAAP for financial reporting purposes, creating a unique research setting in which different sets of accounting standards are put on a level playing field and institutional factors are held constant.

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where IFRS is an indicator variable taking the value of one (zero) for CL IFRS (U.S.) firm-year observations. We interpret the coefficient on IFRS + POST × IFRS as the difference in absolute discretionary working capital accruals between CL IFRS and U.S. firms in the post-elimination period. To investigate the difference in the degree of asymmetric timely loss recognition between CL IFRS and U.S. firms, we run the following regression separately for the pre- and postelimination periods: Eit ¼ β 0 þ β1 Rit þ β 2 DUM it þ β3 Rit  DUMit þ β 4 IFRSit þ β5 IFRSit  Rit þ β 6 IFRSit  DUM it þβ 7 IFRSit  Rit  DUMit þ Year dummies þ Country dummies þ Industry dummies þ ε it :

ð5Þ We interpret the coefficient on IFRS × R × DUM as the difference in the incremental timeliness of bad news over good news between CL IFRS and U.S. firms. Finally, we estimate the following regression model pooling all CL IFRS and U.S. firmyear observations to compare the value relevance of accounting earnings between CL IFRS and U.S. firms: Rit ¼ β 0 þ β 1 Eit þ β 2 POST it þ β 3 Eit  POST it þ β 4 IFRSit þ β 5 Eit  IFRSit þ β 6 POST it  IFRSit þ β 7 Eit  POST it  IFRSit þ β 8 SIZEit þ β 9 Eit  SIZEit þ β 10 BM it þ β 11 Eit  BM it ð6Þ þβ 12 LOSSit þ β 13 Eit  LOSSit þ Year dummies þ Country dummies þIndustry dummies þ ε it :

We interpret the coefficient on E × IFRS + E × POST × IFRS as the differential magnitude of ERCs between CL IFRS and U.S. firms in the post-elimination period. We match CL IFRS firms with a sample of U.S. firms based on year, industry, and sales growth and apply the same sample selection procedure as described in Section 4, leaving 388 and 442 firm-years for the accrual test and the asymmetric timely loss recognition and value relevance tests, respectively. Table 6 presents results for the comparison of accounting quality resulting from applying IFRS by CL IFRS firms and that resulting from applying U.S. GAAP by U.S. firms. Consistent with Gordon et al. (2008), we find that IFRS-based earnings are less value relevant than U.S. GAAP-based earnings in the pre-elimination period. CL IFRS firms' reported earnings also contain more accounting discretion than those of U.S. firms. However, in the post-elimination period, there is no significant difference in the quality of accounting data between CL IFRS firms and U.S. firms. We find only weak evidence that CL IFRS firms recognize gains and losses in a more symmetric manner than do U.S. firms, which is in line with Barth et al.'s (2007) findings. Overall, our results suggest that accounting quality under current IFRS and U.S. GAAP is comparable. 7. Conclusions This paper examines how the elimination of the reconciliation requirement affects the quality of accounting data resulting from the application of IFRS by CL IFRS firms. Using NCL IFRS firms as the control sample, we find that CL IFRS firms exhibit a decrease in the magnitude of accounting discretion, a tendency to recognize gains and losses more asymmetrically, and an improvement in the value relevance of reported earnings after the

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reconciliation requirement is removed. 24 These findings are more pronounced for firms from high enforcement countries, suggesting that firms with higher level of local monitoring have more incentives to minimize the reconciliation differences considering the expected costs arising from regulatory scrutiny. Using the data from the post-elimination period, we find that accounting numbers prepared under IFRS by CL IFRS firms are of comparable quality to those prepared under U.S. GAAP by U.S. firms, except for the asymmetric timeliness of earnings. We contribute to the literature along several dimensions. First, the literature on the elimination of the reconciliation requirement primarily focuses on the capital market consequences of this rule change. We complement the literature by showing how the reconciliation requirement influences CL IFRS firms' incentives in the application of IFRS. Second, given the evolution of IFRS and U.S. GAAP in these years, our results provide the most recent evidence on whether accounting numbers prepared under current IFRS and U.S. GAAP have material quality differences. Finally, our findings on the quality of accounting data prepared using IFRS by CL IFRS firms have implications for the SEC on the potential use of IFRS by U.S. firms. References Ball, R., Robin, A., & Wu, J. S. (2003). Incentives versus standards: Properties of accounting income in four East Asian countries. Journal of Accounting and Economics, 36(1–3), 235–270. Barth, M. E., Beaver, W. H., & Landsman, W. R. (2001). The relevance of the value relevance literature for financial accounting standard setting: Another view. Journal of Accounting and Economics, 31(1–3), 77–104. Barth, M. E., Landsman, W. R., Lang, M. H., & Williams, C. D. (2007). Accounting quality: International Accounting Standards and US GAAP. Working paper. Barth, M. E., Landsman, W. R., Lang, M. H., & Williams, C. D. (2010). Are international accounting standardsbased and US GAAP-based accounting amounts comparable? Working paper. Bartov, E., Goldberg, S. R., & Kim, M. (2005). Comparative value relevance among German, U.S., and international accounting standards: A German stock market perspective. Journal of Accounting, Auditing & Finance, 20(2), 95–119. Basu, S. (1997). The conservatism principle and the asymmetric timeliness of earnings. Journal of Accounting and Economics, 24(1), 3–37. Beaver, W. H., & Ryan, S. G. (2005). Conditional and unconditional conservatism: Concepts and modeling. Review of Accounting Studies, 10(2), 269–309. Bradshaw, M. T., & Miller, G. S. (2008). Will harmonizing accounting standards really harmonize accounting? Evidence from non-U.S. firms adopting U.S. GAAP. Journal of Accounting, Auditing & Finance, 23(2), 233–263. Burghstahler, D. C., Hail, L., & Leuz, C. (2006). The importance of reporting incentives: Earnings management in European private and public firms. The Accounting Review, 81(5), 983–1016. Chen, L. H., & Sami, H. (2008). Trading volume reaction to the earnings reconciliation from IAS to U.S. GAAP. Contemporary Accounting Research, 25(1), 15–53. Collins, D. W., & Kothari, S. P. (1989). An analysis of intertemporal and cross-sectional determinants of earnings response coefficients. Journal of Accounting and Economics, 11(2–3), 143–181. Dechow, P. M., & Dichev, I. D. (2002). The quality of accruals and earnings: The role of accrual estimation errors. The Accounting Review, 77, 35–59 (Supplement). Dechow, P. M., Sloan, R. G., & Sweeney, A. P. (1995). Detecting earnings management. The Accounting Review, 70(2), 193–225.

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