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4 The economic consequences of fair value reclassifications under IFRS

4.1 Introduction

At the peak of the financial crisis in October 2008, the IASB forwent any regular due process to issue an emergency amendment to IAS 39 in order to relax fair value accounting. These amendments leave banks reporting under IFRS with the choice to retroactively reclassify financial assets that were previously measured at fair value into categories which require measurement at amortized cost, i.e. to effectively abandon fair value accounting for these assets. This decision sharply contrstrategy in reporting for financial instruments (IASB, 2008a) and its strong initial position against reclassifications.68 However, the board eventually surrendered to severe political pressure by the EU Commission and EU leaders, most prominently the French president Nicolas Sarkozy. They repeatedly voiced their concerns about the procyclicality that fair value accounting may introduce and requested to align accounting rules for European banks with those that apply to its US competitors, for which a similar reclassification option already existed under SFAS 65 and 115.69 In contrast, opponents of easing fair value rules, such as the British Prime Minister Gordon Brown, who stressed that fair values simply reflect current economic reality, went unheeded.70 This conflict at the top political level in the heat of the financial crisis has been the culmination of a long-time controversial debate in standard setting (e.g. Joint Working Group of Standard Setters, 1999; IASC, 1997) and academics (e.g. Barth, 2006; Landsman, 2007; Ronen, 2008) about the pros and cons of fair value accounting.

Banks made ample use of the opportunity to forgo substantial write-downs of financial assets that had become illiquid during the course of the crisis. For eDeutsche Bank was able to boost its net income for 2008 by 3.2bn Euros by reclassifying troubled assets with a book value of 23.6bn Euros. In effect, since compliance with

ng numbers, the amendment to IAS 39 was politically perceived as a cheap way to put pressure off the troubled banking sector (Bushman and Landsman, 2010), especially because it was no longer politically opportune to force banks into bankruptcy after the Lehman experience

68 See, e.g., Reuters News, Philippe Danjou: Reporting rules should not favour bank cushions, September

11, 2008; Reuters News, David Tweedie: Big rewrite of accounting fair value ruled out, July 10, 2008. 69 See, e.g., , Statement, Summit of European G8 Members, October 4, 2008. 70 See, e.g., Financial Times, Debate to ease fair value accounting intensifies, October 15, 2008.

U. Brüggemann, Essays on the economic consequences of mandatory IFRS reporting around the world, DOI 10.1007/978-3-8349-6952-1_4, © Gabler Verlag | Springer Fachmedien Wiesbaden GmbH 2011

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in September 2008. Yet, the perceived consequential benefits and, perhaps even more importantly, the potential costs of the politically forced decision to allow the suspension of fair value measurement are largely unknown.71

The purpose of this essay is to empirically investigate the economic consequences of

reclassification amendment to IAS 39 has at least two advantages compared with the reclassification option offered by SFAS 65 and 115 to US banks. First, the reclassification option under US-GAAP is hardly used by US banks (Laux and Leuz, 2010). This is due to major differences between the two accounting regimes. The IAS 39 reclassification option is applicable retroactively (at least for the short but highly relevant time window July to October 2008), i.e. banks can reverse already recognized fair value write-downs with the benefit of hindsight. Moreover, impairment rules after reclassification are more restrictive under US-GAAP, i.e. the extent of write-downs that a bank can potentially forego by reclassifying its fair value assets is, ceteris paribus, larger under IFRS. Second, the international setting allows us to exploit cross-country differences in the link between financial accounting and capital regulation to provide insight into how banking regulation has affected accounting choices related to fair value accounting during the financial crisis.

Given the complexities of the short- and long-term consequences the IASB was facing in its decision to allow (or deny) the request for reclassifications of fair value assets, it is beyond the scope of this paper to make any judgment on whether the amendment decision was socially optimal. However, we are able to study and quantify the effects of

-term economic consequences during the extraordinary circumstances of the crisis, and ultimately the long-run effects on information asymmetry and adverse selection when fair value information about financial assets is eliminated from financial statements of banks.

Our analysis proceeds in three steps. First, we provide descriptive evidence on (1) the magnitude and impact of fair value reclassifications on accounting numbers and (2) 71 In fact, standard setters (e.g., House of Commons, 2008) and investor advocates (e.g., CFA Institute,

2008) fear that the actions taken have adverse effects on the information the reporting standards

(IASB Framework, para. 10). In addition, there are significant worries that the interference of the European Commission into the formally independent standard setting process of the IASB poses a major obstacle to further convergence of accounting standards, and in particular the adoption of IFRS in the US, see e.g., Financial Times, Put the brakes on convergence before it is too late, October 30, 2008.

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disclosure practices related to the reclassifications. Using a comprehensive global sample of 302 publically-traded and IFRS reporting banks, we show that more than one third (124 banks) chose to reclassify some assets, thus increasing aggregate profits by a total of 22.7 billion Euros and firm-specific profits by 44% on average (see also CESR, 2009).

substantially affected by the amendments to IAS 39. Further, we document that within the subset of reclassifying banks, only 42 banks fully comply with the newly introduced IFRS 7 disclosure requirements designed to mitigate the informational effects of reclassifications.

In the second step of our analysis, we empirically analyze the factual underlying

the official arguments put forward in the political discussions surrounding the amendment. We document and exploit the cross-country differences in the link between fair value accounting under IFRS and the determination of regulatory capital to provide

-downs. Major differences stem not only from the level of the minimum capital adequacy ratio, but also from the prudential filters applied on unrealized fair value gains of AFS assets (positive revaluation reserves). We find that banks are more likely to reclassify if (1) their total capital ratio before reclassifications is close to the local minimum capital adequacy ratio and (2) the country-specific discount (haircut) on unrealized fair value gains is small, i.e. more regulatory capital is at risk in times of falling market prices. Moreover, a number of system-relevant banks would have faced the risk of immediate supervisory interventions had the amendment or, alternatively, changes to regulatory capital requirements not been adopted. Thus, our findings are consistent with reclassifications granting regulatory forbearance to economically weak banks (see also Skinner, 2008), rather than reducing disadvantages relative to US banks (Laux and Leuz, 2010).

In the third part of our empirical analysis, we investigate both short-term and the long-term capital market reactions to the abandonment of fair value measurement. While in times of high market volatility and uncertainty we cannot detect any robustly positive or

October 2008 or the bank-specific reclassification announcements, but we do find statistically and economically significant positive abnormal returns for banks that are close to violating regulatory capital restrictions. We complement this analysis by showing that market-adjusted buy and hold returns for reclassifying banks are

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significantly higher than for other banks in the following year. Overall, this evidence suggest that the amendment did provide initial relief for banks with financial difficulties, and arguably helped them short-term (along with other policy mechanisms) to recover from the effects of the crisis.

Where the former analyses document crisis-specific short-term benefits due to the link between fair value measurement and banking regulation, it is the question of how a decrease in fair value information affects reporting transparency, i.e. whether the short-term relief comes at long-term costs. We therefore study the long-term changes in information asymmetry by comparing the bid-ask spreads of reclassifying and non-reclassifying banks in a difference-in-differences design. We distinguish between banks that fully comply with the accompanying disclosure requirements and banks that withhold information about the reclassified assets. Our analysis shows that the reclassification of financial assets coincides with an increase in bid-ask spreads if the impact on net income is strong and the corresponding disclosure requirements are not fully complied with. This effect is both statistically significant and economically

relaxation of fair value accounting of financial assets provides bank managers with leeway to reduce the transparency of financial reporting. This decrease in transparency can lead to adverse capital market effects which is particularly critical in times of crisis (Lang and Maffett, 2010). At the same time, we cannot identify any negative effects of the switch from fair value recognition to disclosure per se.

In general terms, our study contributes to the discussion among regulators and standard setters in the current debate on banking supervision and accounting for financial instruments by banks (e.g., Barth and Landsman, 2010; Bushman and Landsman, 2010), in particular on the contracting and informational role of fair value measurement in an international setting (for the US, see e.g. Laux and Leuz, 2009, 2010). We also present evidence consistent with the political cost hypothesis (Watts and Zimmerman, 1978). In this crisis-specific setting, it is, however, upward management of earnings (rather than downward management) which minimizes the costs of future lobbying activities and the risk of adverse regulatory actions. By analyzing what happens when the IASB is forced into a decision by a powerful economic group among its adopting countries (in our setting, the EU), we also contribute to the literature on the politics of standard setting (e.g. Watts and Zimmermann, 1986), particularly adding the supranational dimension a global standard setter is facing (Sunder, 2009). In this respect, the reclassification

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banking lobby groups which take advantage of deviations between IFRS and US-GAAP.

Further, our study contributes to the literature by examining the consequences of a decrease in fair value measurement. Due to the regulatory environment that has increasingly extended the scope of fair value notes disclosures and/or measurement, prior research has exclusively studied potential benefits of increases in fair value notes disclosures (e.g., Nelson, 1996; Barth, Beaver, and Landsman, 1996) or recognition requirements for certain financial instruments (e.g. Ahmed, Kilic, and Lobo, 2006; Hodder, Hopkins, and Wahlen, 2006). In contrast, this study exploits the reclassification amendments to IAS 39 and IFRS 7 and the resulting reclassifications as a unique setting which allows us to analyze the potential costs of decreases in fair value recognition or even notes disclosures.72

Finally, we contribute by exploiting hand-collected and comprehensive data on fair value measurement, notes disclosures and linkages of fair values to national regulatory capital requirements of IFRS banks around the world. Such data is not available in standard databases, which is presumably the reason why there is still little international evidence on the topic (Chang, Liu, and Ryan, 2009), despite the fact that the reliability concerns with fair values should be more serious in countries outside the US where enforcement mechanisms are weak (e.g., Armstrong, Barth, Jagolinzer, and Riedl, 2010; Daske, Hail, Leuz, and Verdi, 2008). We introduce this dataset into the literature on the lessons learned and the regulatory consequences to be drawn from the global financial crisis which, so far, is almost exclusively based on evidence from the US environment (e.g. Bowen, Khan, and Rajgopal, 2009; Huizinga and Laeven, 2009; Song, Thomas, and Yi, 2010).

The remainder of the essay is organized as follows. In section 4.2, we describe the institutional background. In section 4.3, we review related literature and develop testable hypotheses. Section 4.4 describes our empirical strategy, data and results. We provide concluding remarks in section 4.5. Section 4.6 contains the tables.

72 For example, it is far from clear whether (the magnitude of) the effects are simply opposite to the

effects of first-time recognition of fair values, since the valuation techniques are already established and, thus, formerly recognized fair values that are still disclosed in the footnotes after reclassifications should produce information of similar reliability.

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4.2 Institutional background

4.2.1 Events preceding the reclassification amendments

The global financial crisis deteriorated continuously during 2008. Banks around the world were faced with substantial fair value write-downs on their trading and available for sale portfolios. Although a similar development could be observed in almost any developed market, the accounting consequences differed between US-GAAP and IFRS. In the US, the situation has been interpreted as one of the rare circumstances under which SFAS 115 (for securities) and SFAS 65 (for mortgage loans) offer an option to transfer financial assets from the trading or available for sale (held for sale) category into the held to maturity category (i.e. to abandon fair value measurement of the respective assets). Anecdotal evidence indicates that a few prominent US banks did indeed make use of this opportunity (Laux and Leuz, 2010).73 In contrast, banks reporting under IFRS could not avoid the reporting of fair value losses from trading assets that might have lost their

shall not reclassify a financial instrument into or out of the fair value through profit or loss category while it is hel

Commercial banks outside the US identified this restrictive rule, which forced them to report, ceteris paribus, lower profits and lower regulatory capital than US competitors exercising their options, as a severe disadvantage in global capital markets, particularly during the financial crisis. Bank representatives intensely lobbied for the introduction of a reclassification option into IAS 39. In the public domain, the Institute of International Finance (IIF), an organization of international banks, asked the IASB in May 2008 to

conditions, or suggestions that would allow assets to be reclassified from trading to other categories in accordance with define

Ackermann, at the same time head of the IFRS reporting Deutsche Bank, underlined in a

73 According to its 10-K filing (footnote 16), Citigroup, which had rarely used the held to maturity

category before, transferred trading assets at a carrying value of USD 33.3bn and available for sale securities at a carrying value of USD 27.0bn into that category during the fourth quarter of the financial year 2008. T

additional fair value write-downs of approximately USD 4.1bn in 2008.

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US GAAP and IFRS, in order to create a level playing field for international banks .74

In some European countries which have adopted IFRS, particularly in Continental European France, Germany and Italy, the resistance of bank lobbyists towards fair value accounting had gained the support of top-level politicians. Concerns over the reliability and procyclicality of fair value accounting have been the subject of discussions at regular meetings of the EU and Finance Ministers (Economic and Financial Affairs Council, ECOFIN) since November 2007 (ECOFIN, 2007; ECOFIN, 2008a). The skepticism towards fair value accounting might not least be due to the concerns which bank regulators had articulated for years (e.g., ECB, 2004). In the current crisis, regulators have tended to blame fair value accounting for having contributed to the banking turmoil. For example, both the Basel Bank for International Settlements (BIS) and the Financial Stability Forum, two organizations which represent, among others, financial supervisory institutions, later recommended that international accounting

accounting is more limited for financial instrumeForum, 2009).

Initially, the IASB strongly opposed any reduction to the scope of fair value measurement in IAS 39. As a direct response to criticism raised at the ECOFIN meeting in July 2008, IASB Chairman Sir David Tweedie ruled out any rewrite of the then

75. In early September 2008, the here is no support within the banking

76. When the IASB issued a draft of guidelines on fair value measurement in illiquid markets on September 16, one day after the Lehman breakdown, there were still no indications for any short-term changes to IAS 39. The plan was rather to issue a completely new fair value standard in the second half of 2009 (IASB, 2008a).

The Lehman breakdown, however, entirely changed the political situation of the IASB. When international banks faced the risk of reporting substantial losses and due to IFRS accounting numbers being used in the determination of regulatory capital a severe 74 Financial Times, Banks Told to Tackle Risk and Pay. July 18, 2008. 75 Reuters News, David Tweedie: Big rewrite of accounting fair value ruled out, July 10, 2008. 76 Reuters News, Philippe Danjou: Reporting rules should not favor bank cushions, September 11, 2008.

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decrease in their capital ratios for the third quarter of the financial year 2008, politicians, particularly from the EU, substantially increased the pressure on the accounting body to alter IAS 39 in a way that allowed banks to forgo the recognition of those losses. At the summit of European G8 members (France, Germany, Italy, UK) on October 4 in Paris, the Fren

financial institutions are not disadvantaged vis-à-vis their international competitors in terms of accounting rules and of their interpretation. In this regard, European financial institutions should be given the same rules to reclassify financial instruments from the

Members, 2008). During the next week, the ECOFIN and the European Commission

of asset the end of the month, with the objective to implement as of the third quarter, in

Commissioner Charlie McCreevy gave a speech in the European Parliament and -

IAS 39 and was ready to adopt its own EU version of IAS 39 which would allow the reclassification of financial assets but not introduce any disclosure requirements, if the IASB did not alter the accounting standard on its own.

ard did not comply with the

Commons, 2008). The IASB therefore rapidly gave in primarily to prevent a standard that would give European firms the opportunity to abandon fair value measurement without any accompanying disclosures, but also in a desperate attempt to protect the ongoing process towards achieving a single global accounting language. On October 9, one day after the McCreevy speech, the IASCF trustees decided in a public meeting that the IASB was allowed to suspend the normal due process to avoid lengthy consultations before adopting fair value reclassifications. This decision made it possible to finalize an amendment to IAS 39 at the next regular board meeting held on October 13. When the board met that day, an amendment to IAS 39 allowing reclassifications of fair value assets was indeed adopted with the approval of eleven of the thirteen IASB members

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(with dissent by James Leisenring and John Smith). In a press release, the Board stressed

e under which the amendment came about, which had seemed highly unlikely just four weeks earlier.

Only two days later, the EU Commission officially endorsed the amendments. Even though they were adopted in response to European lobbying activities, other jurisdictions where formal endorsement procedures for IFRS had been established also accepted the reclassification rules (October 15, Hong Kong; October 17, Taiwan; October 22, Australia; October 23, Philippines; October 24, South Africa; October 30, Singapore).

4.2.2 The reclassification amendments

4.2.2.1 Amendments to IAS 39: recognition and measurement

The measurement of financial instruments is within the scope of IAS 39, which introduces three different measurement bases: fair value through profit or loss, fair value through OCI, and amortized cost (e.g., Spooner, 2007). Trading assets, among them all financial derivatives not designated for hedge accounting, are unexceptionally measured at fair value through profit or loss. Fair value measurement through profit or loss can also be applied if the fair value option is chosen for an instrument. Amortized cost, on the other hand, is the relevant base for the measurement of financial assets categorized as either loans & receivables (L&R) or, in the case of marketable debt securities, held to maturity (HTM). Financial assets, for which none of these categories is used, are designated as available for sale (AFS) and measured at fair value through OCI. The AFS category of IAS 39 is applicable for both securities (equivalent to the corresponding category of SFAS 115) and loans. The categorization is required at the initial recognition of any financial asset.

After initial recognition, there are five types of possible reclassifications of assets measured at fair value. The original IAS 39 had allowed the reclassification out of the AFS category into the HTM category only (para. 54). The amendment from October 2008 introduces four additional types of reclassifications. Since then, trading assets can be reclassified into either the AFS, HTM, or the L&R category and AFS assets can be reclassified into the L&R category. It is, however, not allowed to reclassify any assets for

derivative. All five typ(paras. 50B, 54), but they differ in their accounting consequences. Overall, three different

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effects on measurement can be distinguished. First, reclassifications out of the trading account into the HTM or L&R category affect both net income and equity because fair value gains and losses cease to be recognized in profit or loss and, thus, in equity. Second, reclassifications out of the trading account into the AFS category affect only net income and not equity because fair value gains and losses are still considered in the

than in profit or loss. Third, reclassifications out of the AFS category into the L&R or HTM category affect only OCI (equity) and not net income because fair value gains and losses have previously not been considered in the income statement, but only in the OCI

The newly introduced rules differ from their US-GAAP counterparts in two important respects. First, all IFRS adopting banks are allowed to apply the relaxed rules retroactively from any date between 1 July and 1 November 2008, i.e. a reclassification could not only be used to avoid expected future fair value write-downs but also to reverse write-downs already been taken for this last quarter. Second, the rules for the recognition of other-than-temporary impairment losses that were to be applied after reclassification into cost categories are substantially less restrictive under IFRS (both for the HTM and the L&R category).77 Therefore, the fair value write-downs a bank could avoid by means of reclassifications are, ceteris paribus, potentially larger than under SFAS 65 and 115. These two reasons might explain why Citigroup is the only major US bank that considerable made use of its options (Laux and Leuz, 2010).

4.2.2.2 Amendments to IFRS 7: disclosures

The IASB primarily responded to the political pressure by its own version of a reclassification amendment in order to avoid an EU-specific carve-out from IAS 39, thus ensuring the simultaneous introduction of disclosures about the use of the option (House of Commons, 2008). These extensive disclosure requirements have been introduced into IFRS 7. The disclosures comprise quantitative information about (1) the amount reclassified into and out of each measurement category, (2) the current fair values of each asset that was previously reclassified, (3) the fair value gain or loss in net income or OCI in the period of the reclassification, (4) the fair value gain or loss after reclassification that would have been reported if the asset had not been reclassified, (5) the effective

77 For this very reason, the two dissenting IASB members expressed concerns that a true level playing

field between IFRS and US-GAAP was not achieved (IASB, 2008b).

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interest rate and the estimated amounts of cash flows expected to be recovered as at the date of reclassification, as well as qualitative information about (6) the facts and circumstances of the rare situation that gave rise to the reclassifications (para. 12A).

4.2.2.3 Consequences for the regulatory capital of banks

To the extent banking oversight and regulatory capital are linked to financial reporting, reclassifications may also affect the regulatory capital which banks report to national supervisory authorities. The effect depends on country-specific regulation, and we detect and document in table 4.6.1 substantial cross-sectional variation in the link between IFRS accounting numbers and prudential filters on the inclusion of unrealized fair value gains and losses into regulatory capital. In almost any jurisdiction, unrealized gains and losses from trading account securities are fully reflected in tier 1 capital. Reclassifications out

one.

The major differences across countries arise from the treatment of unrealized gains from AFS securities which are recognized in the revaluation reserves (via OCI). While unrealized losses (after tax) are fully deducted from tier 1 capital, the Basel II Framework recommends the inclusion of unrealized fair value gains into tier 2 capital with a general discount (haircut) of 55% to reflect both the risk of market illiquidity and the future tax charge (Art. 49(v)). However, supervisory practice across the world differs substantially in the implementation of this guideline. In most jurisdictions, the discount is different for equity securities, debt securities and loans. In our 39 sample countries, an average haircut of 48.23% is applicable for unrealized gains on equity securities (including deductions for tax effects). Gains and losses on loans categorized as AFS are, on the other hand, fully neutralized in the determination of regulatory capital. Debt securities are treated like AFS equity securities in 27 countries and like AFS loans in 12 countries (see CEBS (2007) for an overview of EU member states). Unfortunately, disclosures on financial asset types or portfolio compositions which are subject to reclassifications are not required by IFRS 7. As our best proxy, we therefore report in table 4.6.1 the discount on debt securities for the estimation of the effect of the reclassifications on regulatory capital because evidence from voluntary disclosures by our sample banks suggests that the

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majority of reclassified assets are debt securities. The discount on debt securities varies between 0% and 100% across countries.78

While most jurisdictions apply a net approach in determining the adjustments to the revaluation reserve (i.e. the prudential adjustment is based on the aggregate revaluation reserve), a few regulators (Netherlands, Portugal, Slovakia, Slovenia) require the determination on an item-by-item basis (i.e. the prudential adjustment is determined for each AFS asset individually). Again, IFRS 7 disclosures do not allow us to take this regulatory variation into account and, since regulatory reports are not publicly available in most jurisdictions outside the US, we need to approximate the regulatory effect of reclassifications from or into the AFS category by using the net approach for countries where the item-by-item approach is applied.

Finally, jurisdictions differ in the required minimum capital ratio which defines a

Framework recommends a total capital ratio (tier 1 plus tier 2) of at least 8% (Art. 40). Most countries follow this recommendation, while a few countries require a ratio of 10% or 12% (see table 4.6.1 for details).

4.2.3 Initial reactions to the amendment decision

bate. Unsurprisingly, bank representatives, e.g. the European Banking Federation (EBF), and

79 On the other hand, users of financial statements harshly criticize the new rules. The Corporate Reporting Users Forum, a pan-European group of investors and analysts, argues in a public letter to the Financial Times that the new reclassification option

80 This concern finds

78 For uniformity, we use the total discount (on an after-tax basis) in our analysis, i.e. the combination of

the deduction for tax effects and the additional haircut under national banking laws. See table 4.6.1 for the two components.

79 information (CEBS) refers to the convergence argument brought up by European politicians in a joint statement with the Committee of European Securities Regulators (CESR) and declares that European companies

-(CEBS, 2008).

80 Financial Times, Accounting rule changes could dent confidence, say analysts, October 21, 2008.

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Regulatory Committee as a response to the endorsement decision, expecting that the IAS 2008).

Interestingly, comments in the business press are mostly negative even in countries where politicians strongly lobbied for the new rules. In France, for example, Les Echos

81 and La Tribune criticizes the political influence on the standard setter.82

Part of the criticism is due to concerns that global convergence of accounting standards is decreasing rather than increasing as a result of the IAS 39 amendment. The first reason for this concern is factual because impairment rules for reclassified assets measured at amortized cost are less restrictive under IFRS than under US-GAAP, i.e. it is easier for IFRS adopting banks to avoid additional write-downs once a financial asset is reclassified. The amendment therefore, does not lead to true convergence. The second reason is political, because the history of the amendment has demonstrated that the EU has, in fact, substantial power over the IASB. This experience casts serious doubt on the US accepting or even introducing IFRS for national companies in the near future. The amendment therefore, calls future convergence activities into question83 and the contradicting strategies of the FASB and IASB on fair value accounting in the aftermath of financial crises seem to support these concerns.84

81 (Do not break the thermometer), Les Echos, Ne cassons pas le thermomètre, October 10, 2008. 82

the amendment results in increasing opacity), La Tribune, La Commission rend sa copie sur les normes comptables, October 16, 2008.

83 Getting straight to the point, a financial analyst commented in the Financial Times (October 30, 2008): s done without due process: no comments or discussion were sought from

investors. Incredibly, that suspension of due process bore the blessing of the trustees who oversee the IASB. Seeking convergence on a tiny part of the rules in this regard may seem trivial, but it is a giant step backwards. It shows that when the going got tough, the IASB waived the interests of those - the users of accounts - whom it is supposed to serve. Instead of converging to what is best in US standards, the IASB is adopting some

84 The IASB keeps amortized cost accounting at least for certain loans (IFRS 9), whereas the FASB proposes a full fair value model for financial instruments (ED ASU Topics 815 and 825), see also The Economist, To FASB or not to FASB, June 10, 2010.

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4.3 Hypotheses development and related literature

4.3.1 Short-term benefits of the reclassification choice during the financial crisis

reclassifications (para. 12A (c)) reveals that almost all banks provide cursory and

to the general market turmoil during 2008. Therefore, our hypotheses development relies on positive accounting theory (e.g., Holthausen and Leftwich, 1983; Watts and Zimmerman, 1986) which offers a host of alternative explanations for the reclassification choice.

Most importantly, fair value reclassifications of illiquid financial assets potentially infalling market prices. Thus, management incentives for fair value reclassifications may result from regulatory capital restrictions that are tied to accounting measures. In times of the worst financial crisis for decades, this appears to be a likely first order effect.

risk of regulatory costs that would be incurred if restrictions were violated and supervisory actions were taken. These regulatory measures can take various forms, up to a forced closure of the bank, may vary across countries, but always result in a substantial loss of shareholder value. For example, Jordan, Peek, and Rosengren (2000) provide evidence that share prices of US banks drop, on average, by about 5% around the announcement of formal supervisory actions against the bank. In banking crises, discretion offered by or introduced into accounting standards is an implicit means of regulatory arbitrage to satisfy the necessary thresholds, thus granting banks the avoidance of these costs without explicitly exposing this fact to the public (Skinner, 2008). Taken together, there is broad prior evidence that commercial banks manage their capital ratios (e.g. Beatty, Chamberlain, and Magliolo, 1995; Ramesh and Revsine, 2001). We conjecture that if a bank faces the risk of regulatory costs, i.e. is weakly capitalized, it is likely that it will use fair value reclassifications to increase its regulatory capital during the financial crisis.

Even though the Basel Accords aim to harmonize global banking regulation, there are still notable institutional differences in the determination of regulatory capital across countries (see table 4.6.1 for details). The most relevant difference in our setting, aside from the level of the minimum capital adequacy ratio, is the inclusion of positive

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revaluation reserves into tier 2 capital. If an AFS asset is reclassified, the revaluation reserve is frozen at the level of the reclassification date and the extent to which the reserve will be included in tier 2 capital is safeguarded against future decreases in fair value (at least if the fair value decreases are not causing simultaneous impairment write-downs). The lower the haircut on unrealized gains from AFS securities (see section 4.2.2 for details), the more regulatory capital is therefore at risk when a bank expects a decrease of the fair value of its AFS assets. Thus, we hypothesize that the haircut on the revaluation reserves adds to the probability that a bank will apply the reclassification option for regulatory capital arbitrage in order to satisfy necessary capital thresholds.

We expect a bank to also consider expected political costs in its reclassification decision, even though this link to the reclassification choice is more tentative than any of the other links. In short, the reclassification amendment was the result of political pressure by governments (particularly from Continental Europe) put on the IASB, which can be traced back to intense lobbying activities by banks (see section 4.2.1). Although prior evidence on the political cost hypothesis (Watts and Zimmerman, 1978, 1990; Holthausen and Leftwich, 1983) suggests that earnings are managed downward to avoid costly political or regulatory interventions (e.g., Ramanna and Roychowdhury, 2010), matters were quite different for banks during the 2008 financial crisis. In this particular setting, political incentives may rather act in favor of reclassifications, i.e. of upward management of earnings, for two reasons. First, their stabilizing effect on regulatory capital helps to avoid adverse political actions that are associated with governmental bail-outs. Since bail-outs are highly unpopular among the majority of voters, they are accompanied by tight restrictions on the business of a bank and, maybe most importantly,

85 Second, if banks did not make sufficient use of the newly introduced option they intensely lobbied for, it would most probably increase the costs of opposing adverse political actions and decrease the likelihood of the success of future lobbying activities for certain accounting rules. This prediction is consistent with Ramanna (2008), who for goodwill impairment rules prior to the adoption of SFAS 142 was positively

-adoption use of accounting discretion offered by the new rules. The firm-specific size of the political incentives, therefore, are likely to depend on the extent to which the national government has been involved in the lobbying process and how much public attention the bank received during that process.

85 See, e.g., Financial Times, How to bypass populism and tackle banking, January 26, 2010.

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In addition to these firm-specific considerations, governments might have their own

income and/or shareholders equity during the financial crisis can be viewed as a stabilization of the financial system, thus reducing costs eventually borne by taxpayers from a continued destabilization and its adverse economy-wide effects. Second, governments in several countries directly injected tax money into large and system-relevant banks, which would have been lost if a bank had been closed after failing to

equity stake, the higher the probability that benefits from a stabilization of the financial s reclassification decision.

least zero earnings (i.e. to avoid the disclosure of an accounting loss). The zero earnings threshold is particularly important in the banking industry where the sensitivity of

bank runs (e.g., Spiegel and Yamori, 2007; Goldberg and Hudgins, 2002) and where the zero earnings threshold has been shown to be of psychological importance for private depositors (Shen and Chih, 2005).86 Since bank failures are not only costly for immediate stakeholders in that bank, but also tend to cause contagion of other banks or even of other economic sectors, the political pressure for the reclassification option can also be interpreted as the intention of national governments to convince the public that banks were healthy. We therefore conjecture that a possibility to pass the zero earnings threshold by means of reclassifications is positively associated with the probability of a

deposits. A bank that already faces a decrease in deposits will be even less inclined to report a loss that coul

The relevance of the zero earnings threshold for measures of regulatory forbearance relies on the assumption of functional fixation by depositors. Since depositors are, on average, lay investors, it is plausible that they do not distinguish between income before and after reclassifications. In contrast, it is less plausible that reclassifications are also

e.g., Degeorge, Patel, and Zeckhauser, 1999; Barth, Elliott, and Finn, 1999; Bartov, 86 Note that this relevance may also hold when there exists deposit insurance or a widespread belief in

governmental interventions resulting from a too-big-to-fail policy exist because even these measures create transaction costs for customers and might not avoid temporary frictions during which access to deposits is restricted.

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Givoly, and Hayn, 2002). Professional investors and financial analysts are substantially less prone to functional fixation than depositors and are likely to use IFRS 7 reconcreclassification effects.87 There is plenty of evidence that market behavior is inconsistent with functional fixation, at least for substantial and less complex accounting choices (Kothari, 2001; Plumlee, 2003). Therefore, contrary to prior findings about the

, Degeorge, Patel, and Zeckhauser, 1999; Bartov, Givoly, and Hain, 2002), it is questionable whether the proximity of pre-reclassification earnings to consensus EPS forecast targets causally

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Our first hypothesis can be summarized as follows:

(H1a) The probability of a bank using the reclassification option is positively associated with the size of the bank-specific benefits from avoiding (a) the violation of regulatory capital restrictions, (b) political costs and (c) a loss of depositors.

reclassification choice, the stock price reaction around the event dates should be positively (negatively) associated with the size of those benefits (costs). With respect to

ement of the amendment to IAS 39 in October 2008 granting banks the reclassification option and (2) the announcement date of the bank-specific choice. While the latter date resolves the uncertainty about the accounting effects for a bank, investors will already have built

Around the regulatory announcement, the abnormal returns of banks that are expected to use the reclassification option should, therefore, reflect the market expectation of any resulting net economic consequences. Recent evidence on fair value regulation in the US suggests an overall positive reaction of the stock market towards the perceived relaxation

87 Some anecdotal evidence can indeed be found in analyst reports and Q3 and Q4 2008 conference call

transcripts. For example, in a JP Morgan report about the German Aareal Bank, the first key point on

t conference call, the same analyst explicitly asks the Aareal Bank

on asset- provided for at least 29 reclassifying banks in our sample.

88 This latter variable could only come into play if management compensation were bound to achieving r role in

2008 accounting choices due to the extraordinary circumstances of the financial crisis.

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of fair value rules, e.g. the adoption of FSP FAS 157-3 in October 2008 (Huizinga and Laeven, 2009) or FSP FAS 157-4 in March/April 2009 by the FASB (Bowen, Khan, and Rajgopal, 2009), at least in times of the crisis. Returns around the bank-specific announcement of the reclassification choice provide an updated measure of the market assessment of the economic benefits and costs. In sum, we hypothesize:

(H1b) The stock price reaction to the announcement of fair value reclassifications is positively associated with the size of the (potential) bank-specific benefits resulting from reclassifications.

4.3.2 Long-term costs of the reclassification choice

environment to its cost of capital via the adverse selection component of the bid-ask spread when market makers price-protect against informed traders (e.g., Stoll, 1978; Glosten and Harris, 1988; Diamond and Verrecchia, 1991). This theoretical link has been supported by a number of empirical studies (e.g., Leuz and Verrecchia, 2000; Muller and Riedl, 2002; Frankel and Li, 2004; Mohd, 2005; Verrecchia and Weber, 2006). These

information asymmetry and cost of capital depend, ceteris paribus, on whether the relaxation of fair value accounting is perceived as a decrease in disclosure quality. Overall, there is consensus that the value relevance of financial assets benefits from fair value disclosures (Barth, 1994; Barth, Beaver, and Landsman, 1996; Eccher, Ramesh, and Thiagarajan, 1996; see Wahlen et al., 2000, for an overview). Moreover, evidence from surveys conducted by the CFA Institute (2008) indicates that financial analysts consider fair value information to be useful. These findings suggest that the use of the reclassification option may signal a decrease in transparency, at least if a bank had previously built up some reputation for its high reporting quality and if the reclassifications affect the accounts in a material way. Stated differently, we predict a positive association between information asymmetry and the size of the effects of fair value reclassifications (e.g. on net income). Managers will anticipate those adverse effects of the reclassification choice and weigh off the corresponding increase in cost of equity capital and in trading costs against the benefits discussed in section 4.3.1. Therefore, we hypothesize:

(H2a) The probability of a bank using the reclassification option is negatively associated with its commitment to transparency.

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The disclosure requirements of IFRS 7 that are applicable in the case of fair value reclassifications ensure that fair value information is still available in the financial statement. Consequently, if disclosure requirements are fully complied with, the relaxation of fair value rules merely results in formerly recognized fair values now being disclosed in the footnotes. Since the different effects of recognition and disclosure are controversial (see Bernard and Schipper, 1994; Schipper, 2007, for a conceptual discussion), the existence of the capital market effects towards fair value reclassifications is not clear ex ante. Due to differences in the quality of enforcement and auditing institutions across countries, however, our international setting offers large heterogeneity in the degree of compliance with the IFRS 7 disclosure requirements. We exploit this variation in the quality of footnote disclosures to distinguish between banks which reclassify and fully disclose the effects and banks which reclassify but do not fully disclose. For the latter group of banks, theory suggests that we should observe an increase in information asymmetry and, thus, adverse selection. Our hypothesis can be summarized as follows:

(H2b) The use of the reclassification option information asymmetry component of the bid-ask spread. The size of the increase is negatively associated with the quality of accompanying footnote disclosures.

4.4 Empirical analysis

4.4.1 Sample selection and data sources

BvD Bankscope is the primary source and starting point for our sample selection. In the first step, all 2,254 banks with publicly listed equity shares are selected (LISTINS). 594 banks from this Bankscope universe can be identified as IFRS adopters (ACCSTAND)89 for the financial year 2008. Next, we augment and verify the global representativeness of this sample by consulting Worldscope and Compustat Global as additional references. We identify and incorporate another 108 banks (Industry Groups 4310 and 4320) reporting under IFRS through these sources. This combined superset is 89 Consistent with the approach in Daske, Hail, Leuz, and Verdi (2009), we check and modify the

Bankscope ACCSTAND coding in two respects: First, we treat banks from Taiwan as IFRS adopters even if they are classified as Local GAAP adopters, because Taiwanese SFAS 34 and 36 largely correspond to IAS 39 and IFRS 7, respectively; both standards have been effective since 2006 and the reclassification amendments were endorsed immediately on October 17, 2008. Second, we change the classification of banks from Malaysia from IFRS to Local GAAP, because the Malaysian Accounting Standards Board has decided that FRS 139 and FRS 7, which are the equivalent standards to IAS 39 and IFRS 7, were not effective before 2010.

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matched with capital market data from Thomson Reuters Datastream; 264 banks are excluded due to missing or incomplete market data for the periods of interest between October 2008 and June 2009 (for bid-ask spreads) and between January 2008 and March 2009 (for stock returns).

Thus, our initial sample comprises 438 banks. Even though IAS 39 is not an industry-specific standard and the reclassification option can be used by any company applying

balance sheet typically consists of financial instruments. The banking industry is, therefore, most strongly affected by IAS 39.90 Second, the effects of the reclassification amendments on accounting choices are likely to be idiosyncratic in the banking industry because its capital regulation is fundamentally different from other industries (even from the insurance industry). Therefore, the inclusion of non-banking firms in our sample would pose the severe issue of largely inhomogeneous accounting incentives. For this second reason, we exclude 112 institutions from our final sample which are not subject to an external capital oversight (hedge funds, brokerage houses, and securities firms which are listed as banks in Bankscope), for which we cannot retrieve any data on regulatory capital (neither manually from the financial report nor via our three databases) or that do not determine regulatory capital on the basis of their IFRS financial statements (due to country-specific options). The manual collection of financial statements from corporate websites reveals that 24 banks from our initial sample do not publish a financial report in English, French, German or Chinese on their websites. These banks are excluded due to practical impediments. Thus, our total sample comprises 302 banks from 39 countries.

We use a variety of data sources for our empirical analyses. Capital market data is obtained from Thomson Reuters Datastream. Accounting data is obtained from Bankscope and Worldscope. While these two commercial databases provide information about the general asset and liabilities structure of each bank (e.g. cash, trading securities, investment securities, loans, non-financial assets), they do not offer any data on fair value reclassifications under IFRS. We therefore manually collect detailed information on reclassification choices and relevant disclosures from the footnotes to the annual financial statements and all previously filed quarterly financial statements for reporting periods which end between October 2008 and September 2009. In total, we evaluate 544

90 This is the prime reason why most prior studies on fair value accounting focus on the financial

industry (see section 4.3). Moreover, there is recent evidence for IFRS firms that the magnitude of fair values outside the financial industry is rather small (Christensen and Nikolaev, 2009).

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quarterly, interim and annual reports. In addition, we use Dow Jones Factiva as well as LexisNexis to identify threclassification choice. If a public announcement (e.g. in a separate press release or in combination with the general earnings release) is not available, we define the official filing date of the complete financial statement (containing the footnote disclosures on reclassifications) as the reclassification announcement. The resulting dataset includes (1)

option, (2) the reclassification amounts for each financial instrument category, (3) the reclassification effects on net income and other comprehensive income (revaluation reserves) for each financial instrument category and (4) information with regard to the type and quality of disclosures related to the reclassification choice.

to collect data on country-specific capital regulation. We use the CEBS (2007) report on prudential filters for regulatory capital in European countries to update and broaden the information from the Barth, Caprio, and Levine (2001) World Bank dataset. Moreover, we contact bank regulators from each of the 39 countries represented in our sample (see table 4.6.1 for details) to verify our information on the supervisory rules governing the determination of regulatory capital. In particular, we document the proportion of the revaluation reserves, i.e. the net amount of unrealized fair value gains or losses on AFS

4.2.2 for details).91 If a national regulator requires an additional haircut for future tax charges on unrealized gains, we refer to the OECD tax survey for the country-specific tax rate. This information allows us to determine precise country-specific capital adequacy ratios necessary to estimate firm-specific proxies for regulatory capital management incentives.

4.4.2 Descriptive evidence

4.4.2.1 Accounting effects of the reclassification amendments

Table 4.6.1 presents details on the sample composition by country as well as selected country and bank variables. More than one third of our sample (124 banks altogether) chose to take the reclassification option during financial year 2008. This proportion is very similar to Fiechter (2010) but lower than the 61% as reported by CESR (2009) for

91 We also asked whether the amendments to IAS 39 had provoked any regulatory changes to the

determination of regulatory capital. However, none of the responding authorities indicated that this was the case.

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EU-banks only, with the difference being due to the different regional composition of our global sample. As described in section 4.2.2, there are three general types of reclassifications. We observe that 97 of the 124 reclassifying banks take the option for trading securities, while 72 banks reclassify AFS assets. Among the banks that reclassify trading securities, 40 institutions transfer assets into cost categories (HTM or L&R), 30 institutions transfer assets into the AFS category and 27 institutions transfer into both categories. These results are quite similar to CESR (2009), suggesting that the distribution of the reclassifications is not EU-specific once a bank takes the option.

Table 4.6. y accounting figures are quite substantial. The evidence indicates that the avoidance of the recognition of fair value decreases is only offset to a very limited extent by impairment write-downs on the assets now measured at amortized cost, suggesting that banks (and their auditors) treated the declines in value as temporary. On average, net income is EUR 182.96m or 43.8% higher after reclassifications. Earnings per share increase by an average of 0.57 Euros per share or 26.9%. The distribution of the effect is, however, highly skewed. Almost every bank increases its net income for the financial year. Only six banks experience a modest decline in net income as a result of the reclassifications, i.e. fair values of formerly reclassified assets exceed amortized costs at the balance sheet date.92 The majority of banks report moderate increases in their net income after reclassifications. For 47 banks this increase is less than 10% of net income before reclassifications. A few banks experience huge percentage increases of up to 1,100%,

Royal Bank of Scotland reports the greatest increase in income of EUR 3,587.0m,

before reclassifications into a profit after reclassifications93 and 13 (11) banks would have

92 These negative effects are small in magnitude and relative to total net income for all six banks with

-2.67m) and the Union Bank of Taiwan (EUR -4.32m) reporting the highest reclassification losses. The effects are likely due to the retroactive application of the option which was limited until 1 November 2008, i.e. an (unexpected) increase in the fair value of reclassified assets between 1 November and the next reporting date (generally 31 December 2008) could not be recognized in profit or loss, thus resulting in a negative impact of the reclassifications on

93 These banks are Crédit Industriel et Commercial (France), Danske Bank, Sparekassen Faaborg

(Denmark), JSC Rosbank (Russia), Pohjola Pankki (Finland), Boubyan Bank (Kuwait), Banca Generali and Mediobanca (Italy).

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EPS forecast if they had not reclassified any financial assets.

Since only net income is affected by the reclassification of trading securities, the effect

securities, is even larger (EUR 287.07m on average). EUR 104.11m of this increase in

from increases in retained earnings, i.e. from net income. The effect on revaluation reserves is, however, more complex, because reclassifications out of the trading account into the AFS category and reclassifications out of the AFS category into cost categories (L&R or HTM) have opposite effects on those reserves. The 33% of the reclassifying banks in our sample that report a net decrease in revaluation reserves after reclassifications have simply shifted fair value losses from net income to OCI (thus, revaluation reserves) and as many as 25 banks have exclusively reclassified trading securities into the AFS category, i.e. safeguarded their net income (retained earnings) at the expense of their revaluation reserves with no effect on total equity. In our sample,

reserves after reclassifications (EUR 829.8m). On the other hand, we also observe that several banks substantially increase their net revaluation reserves and, thus, their

This observation already provides some anecdotal evidence that the reclassification of AFS securities was primarily used to safeguard regulatory capital and to avoid regulatory interventions, dependent on the country-specific inclusion of fair value gains from AFS securities into the determination of tier 2 capital (see section 4.2.2). In terms of magnitude, the average impact of reclassifications on regulatory capital is, however, small when compared with the effects on income. The total capital ratio (tier 1 ratio) increases after reclassifications by an average of 24 (17) basis points or 2.61% (2.05%). Hence, it seems that enduring positive effects of fair value reclassifications on regulatory capital are confined to a relatively small number of banks, some of which, however, are system- 94 There are at least two banks in the sample (Cyprus: Marfin Popular, Jordan: Ahli Bank) that would have had even more difficulty meeting the regulatory capital requirements at the end of the reporting period if they had not reclassified any financial assets.

94 We approximate that seven banks in our sample increase their regulatory capital (total capital ratio) by

more than 100 basis points.

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4.4.2.2 Footnote disclosures of reclassifications

Although the reclassification amendments to IAS 39 affect the measurement of ing

amendments to IFRS 7. A closer look into published financial statements of banks around the world reveals that disclosures about reclassifications are twofold. First, almost every bank makes a binary statement in the description of its accounting policies about whether it has applied the reclassification option for some financial assets. Second, reclassifying banks include the then required IFRS 7 disclosures in additional footnotes. However, compliance with these disclosure requirements varies significantly across countries and banks. Only 42 reclassifying banks (34%) in our sample fully comply with all six requirements laid out in the standard in the first annual report following the amendments (Complete Disclosure, see table 4.6.1). In several countries (Australia, Austria, Finland, Kuwait, Norway, Poland, Portugal, Saudi Arabia, Slovenia, Spain, Turkey, United Arab Emirates), all reclassifying banks violated at least one disclosure requirement. These findings are in accordance with CESR (2009), suggesting that compliance with certain disclosure requirements of IFRS 7 is far from perfect.95

Further analyses based on reclassification disclosures show that IFRS 7 disclosure practice varies by reclassification type (see table 4.6.4, panel A) and is also diverse in the location and format of the information presented.96 Table 4.6.4, panel B, relates Complete Disclosure to various country and bank variables that proxy for the quality of governance and enforcement mechanisms as well as other incentives for transparent reporting. Univariate analyses reveal that IFRS 7 compliance is significantly higher in countries with a developed capital market (Log(MCAP/GDP)) or governance system (CGI Score) and in Member States of the EU (EU Country). IFRS 7 compliance is significantly lower in developing economies (Emerging Country) and in code law countries (Code Law Country). The variable FV in Political News is positively related to Complete Disclosure.

95 The finding that required disclosures are not adequately enforced mirrors the earlier literature on

compliance, particular in the case of IAS/IFRS (e.g., Cairns, 1999; Street and Gray, 2001; Ball, Robin, and Wu, 2003; Brown and Tarca 2005; Ball, 2006). Given the public awareness and political controversy of the reclassification amendment, along with its significant effects on the accounts (see sections 4.2.1, 4.4.2), it is, however, even more surprising that many banks (still) get away with substantial non-compliance with disclosure requirements.

96 26 reclassifying banks (21%) choose to report the reclassifications in a separate footnote, while the remaining banks disclose the information as a footnote to a previously existing footnote. 72 banks (58%) disclose at least part of the information in a clearly arranged table. The other banks rely exclusively on verbal explanations in text format.

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This result suggests that full compliance with IFRS 7 is in fact higher in countries where the fair value debate was influenced by politicians and closely followed by the media, i.e. where the topic attracted more public attention. At the bank level, Complete Disclosure is positively related to the quality of the auditing process (Big 4 Auditor)97, the number of analysts (Analyst Following), the number of shares that are not closely held (Free Float), prior commitment to transparency (Earnings Quality) and bank size (Log(Total Assets)).98 These results are similar in the multivariate analyses, although some variables lose their statistical significance. In sum, our analyses provide evidence that IFRS 7 compliance is positively related to the quality of governance and enforcement mechanisms at bank- and country-level and that public awareness of this accounting issue has fostered full disclosure policies.

4.4.3 Economic and political drivers of the reclassification choice

4.4.3.1 Research design

In our first set of analyses, we run the following probit regression to provide evidence on the determinants of the firm-specific reclassification choice:

(AFS)Recl_Dummy = 0 1 Regulatory Costs 2 Political Incentives + 3 State Ownership 4 + 5 Earnings Quality j Controlsj (4.1)

We estimate two different specifications with regard to the dependent variable. In the first specification, we use Recl_Dummy as a dummy variable that takes a value of one if the bank reclassifies either trading or AFS assets. In the second specification, the binary dependent variable is AFSRecl_Dummy and equals one if the bank reclassifies exclusively AFS assets. We estimate the determinants of AFS reclassifications separately because AFS assets feature some idiosyncratic characteristics with respect to capital regulation.99 costs, political costs, earnings targets, commitment to transparency) and opportunities

97 Only eight reclassifying banks are not audited by one of the Big 4 auditors. Seven of them do not fully

comply with the disclosure requirements of IFRS 7. 98 Note that seven reclassifying banks are cross-listed in the United States and therefore registered with

the SEC. All of these banks provide complete IFRS 7 disclosures. Therefore, a cross-listing/SEC variable cannot be estimated in the probit analyses.

99 In contrast, all results for reclassifications out of the trading account only correspond highly with our findings for the general reclassification choice and are not reported for brevity.

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(state ownership, percentage of trading and AFS assets, country-level enforcement) to use the reclassification option.

Regulatory costs are captured by two different variables. First, Regulatory Capital Restriction is the difference between the minimum capital ratio at country level (as presented in table 4.6.reclassifications, i.e., a higher value is representing a tighter restriction and, thus, a higher probability of regulatory costs. Second, Regulatory AFS Haircut is the proportion of unrealized available for sale (AFS) securities gains included in the determination of total regulatory capital (tier 1 plus tier 2). The variable is regulated by national banking supervisors (see table 4.6.1 for a presentation at country level) and, when necessary under

reserves. The higher this proportion, the more regulatory capital will be safeguarded by a reclassification, i.e., the costs of not reclassifying are higher.

The political costs are measured by the interaction term Political Incentives which IIF Membership) and the political response to

these activities (FV in Political News).100 IIF Membership indicates whether a bank is member of the IIF. Since the IIF had a leading role in the lobbying for reclassifications, we assume that member firms support its position on fair value reclassifications.101 FV in Political News reflects how often top-level politicians (precisely, the president, king, prime minister, secretary of treasury, and secretary of economic affairs) publicly comment on fair value accounting issues between January and October 2008. We collect this information from Google News for each country in our sample. Political Incentives has a value of one if both variables take values larger than zero and of zero otherwise. The direct governmental influence on the reclassification choice is separately proxied for by the governmental equity stakes in a bank (State Ownership).

No Loss Target is a dummy variable which takes a value of one if net income before reclassifications is smaller than zero and the greatest in-sample difference between net income after and net income before reclassifications, i.e., it indicates whether it is technically possible for a bank to pass the zero earnings threshold by means of fair value 100

because the reclassification amendment was adopted without due process. Public commenting of the rules was therefore absent.

101 In fact, the US-based investment bank Goldman Sachs left the IIF in May 2008, because it did on fair value accounting; Financial Times, Goldman set

to sever IIF links, May 23, 2008.

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reclassifications. Since we hypothesize that the incentive to avoid the reporting of a loss, among other incentives, stems from attempts to stabilize customer confidence, the interaction term is constructed as a binary variable which equals one if the sign of the change in customer deposits (Deposits) is negative and No Loss Target has a value of one.102 When the interaction term is included, the two basic terms (No Loss Target and ) are excluded from the model specifications to facilitate the interpretation of the coefficient (e.g., Ai and Norton, 2003).

Earnings Quality sdenotes the average abnormal loan loss provisions since IFRS adoption. We use an established approach (e.g., Beatty, Ke, and Petroni, 2002) to estimate the nondiscretionary portion of the loan loss provision by regressing loan loss provisions on loan loss reserves (t-1), net charge-offs, the change in non-performing loans between t-1 and t, as well as size (measured as the natural logarithm of the book value of total assets). All variables (except size) are scaled by total assets. However, BvD Bankscope does not contain the composition of loans by regions or by customers for the majority of international banks (Gebhardt and Novotny-Farkas, 2010). Therefore, we cannot control for these factors. The variable takes a value of one if a bank does not use loan loss provisioning to inflate its earnings (i.e., if the cumulative residuals are positive), and zero otherwise.

Consistent with our first hypothesis, we expect the coefficient estimates on Regulatory Costs (Regulatory Capital Restriction)103, Political Incentives, State Ownership, and No

1 2 3 4 > 0. Consistent with our second hypothesis, we expect the coefficient estimate on Earnings Quality 5 < 0.

We include three different sets of control variables. The first variable controls for the incentives to reduce income volatility by means of reclassifications. If banks attributed income volatility to fair value accounting, a bank with more volatile income should be more likely to use the reclassification option. We define Income Volatility as a dummy

-yearly percentage 102

targets affect the reclassification decision. The coefficient estimate on the consensus forecast is insignificant in all specifications.

103 When AFSRecl_Dummy is the dependent variable, there is, however, an opposite effect of Regulatory AFS Haircut.

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change in net income between 2004 and 2009. The presentation of IFRS income statements before IFRS 7 adoption in 2007 does not allow us to restrict this variable to net changes in fair values. The variable is irrelevant for reclassifications out of the AFS category which do not affect net income.

The second set relates to the fact that IAS 39 allows reclassification only if a trading or at least selling intention for a specific asset has ceased due to a loss of market liquidity. We therefore expect that a bank is more likely to use the reclassification option if its assets became illiquid during the financial crisis. We use the sum of trading and AFS

decreasing market liquidity (% Securities).104 In addition, we construct a summary Exposure to Crisis).

between January and September 2008 (Stock Return 2008volatility between January and September 2008 (Stock Return Volatility 2008) and (3) a binary variable that indicates whether a bank reports engagements in securitizations in its financial statement (Securitization Activity).105

The third set of control variables acts as a proxy for institutional differences across countries. We use EU membership (EU Country), an aggregate governance score from the World Bank (CGI Score), and the development of the capital market (Log(MCAP/GDP)). We do not have any priors as to how these variables affect the reclassification choices.106

4.4.3.2 Empirical findings

Table 4.6.5 reports the results of multivariate probit regressions. Our analyses provide

104 We acknowledge that this relationship is mechanical, because reclassifications out of fair value

categories are by definition impossible if a bank had not used those fair value categories previously. 105 We use securitization activity for two reasons. First, securitized loans suffered from market illiquidity

during the financial crisis. Second, our analysis of the segment reports shows that securitization activity is correlated with investment banking activities (rho = 0.224, p < 0.001), which were most strongly affected by the market turmoil.

106 Since reclassifications are, as a consequence of the amendments to IAS 39 and IFRS 7, an absolutely permissible means of accounting choice, which cannot be mitigated through restrictive auditing or enforcement procedures, there is no unambiguous channel through which high quality enforcement or auditing could attenuate the magnitude of earnings management through reclassifications. Rather, these variables are of particular importance in the degree of compliance with the IFRS 7 disclosure requirements (Holthausen, 2009; see also section 4.4.4.2).

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the country-specific minimum capital ratio, the higher the probability of a reclassification (either trading or AFS). For example, unreported univariate tests show that the distance of a non-average, more than 50% higher than the one of a reclassifying bank (650 versus 429 basis points, p<0.01). In the multivariate analyses, the coefficient estimate on Regulatory Capital Restriction is statistically significant at the 1%-level showing the expected positive sign throughout all model specifications. The marginal effects indicate that a decrease in the total capital ratio by 100 basis points is associated with an increase in the reclassification probability of two percentage points. Thus, the reclassification probability of a bank with a capital ratio of exactly the minimum adequacy level is, ceteris paribus, approximately 11 percentage points higher than of the average bank in our sample with a capital ratio of 555 basis points above the minimum level and even 66 percentage points higher than of the bank with a capital ratio equal to the first percentile in our sample (3300 basis points above the minimum level). These figures demonstrate that the effect of capital regulation on accounting choice is not only statistically significant but also economically substantial.

In addition, the analysis of AFS reclassification in which we can exploit cross-country differences in the inclusion of unrealized fair value gains into regulatory capital underlines the importance of contracting incentives from capital regulation for the reclassification choice. The discount on unrealized fair value gains required by national banking law (Regulatory AFS Haircut) is negatively associated with the choice to reclassify AFS assets, suggesting that the incentive to reclassify AFS assets is decreasing with the extent to which the unrealized gains are excluded from the determination of regulatory capital, i.e. the incentive is particularly small when reclassifications cannot serve to safeguard regulatory capital due to country-level bank regulation. More specifically, a regulatory switch from a 0% to a 100% haircut on unrealized AFS gains reduces, ceteris paribus, the probability of reclassifications by approximately 15 percentage points

Second, our results provide evidence that political incentives determine the reclassification choices of banks. The coefficient on Political Incentives is positive and statistically significant in all models specifications. Unreported univariate analyses further suggest that both components (IIF Membership and FV in Political News) contribute to this finding. Consistent with the political cost hypothesis, a bank is more likely to reclassify if it is a member of the IIF, i.e. was at least indirectly involved in

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lobbying activities for the new rules, and is from a country with a high degree of political involvement in the fair value debate, i.e. where its accounting choice was more likely to receive a broad level of public attention.

Third, the zero earnings target (No Loss Target) determines the reclassification choice, although the individual coefficient estimates is not strongly statistically significant. In contrast, the interaction term is significant at the 1%-level throughout all model specifications suggesting that the zero earnings target is of particular importance for banks which are already exposed to a loss of depositor confidence. This latter finding is also consistent with reclassifications serving the political objective to grant regulatory forbearance to economically weak banks.

Earnings Quality) loads in the hypothesized negative direction, suggesting that banks with more transparent reporting history are less likely to reclassify. This finding might also indicate how banks evaluate the usefulness of fair value recognition for investors (despite their position in the lobbying process).

Taken together, our results provide support for hypotheses (H1a) and (H2a) according to which perceived benefits from avoiding supervisory interventions, adverse political actions and a loss of depositors as well as perceived costs from a decrease in transparency

variables have the expected signs and are statistically significant in most specifications (except controls for the quality of country-level institutions).

4.4.4 Stock price reactions to reclassification announcements

4.4.4.1 Research design

In this section, we test hypothesis (H1b). In order to

would be to proceed with a formal analysis of the stock market reaction to the announcement of the amendment (e.g., Dechow, Hutton, and Sloan, 1996; Zhang, 2007) or to look at the market-wide reactions to the events which increased or decreased the likelihood in the run-up to the regulatory change (e.g., Armstrong, Barth, Jagolinzer, and Riedl, 2010).107 However, the reclassification amendment we examine was not the result 107 In a similar setting, Beatty, Chamberlain, and Magliolo (1996) and Cornett, Rezaee, and Tehranian

(1996) study the market reaction of commercial bank shares to regulatory announcements increasing the extent of fair value disclosures in the US. While Beatty, Chamberlain, and Magliolo (1996)

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of a long-term process, but rather the culmination of dramatic events within a few days at

did not have a week, we had only a matter 2008). However, Armstrong, Barth, Jagolinzer, and Riedl (2010) analyze an environment without any discernible pattern of good or bad news during their sample period, whereas the confounding events during the few days in October 2008 that are relevant for our setting are tremendous. The reclassification amendment was adopted less than one week after the announcement of part-nationalizations of large UK banks such as Barclays, HBOS, Lloyds TSB and RBS. On October 13, the day of the IASB decision, the Financial Times reports that European governments (among them France, Germany, and the UK) pledge a total of USD 2,546bn in guarantees for new bank debt as part of coordinated plans to rescue their financial sectors. At the same time, the European Central Bank, the Bank of England and the Swiss National Bank announced unlimited capital injections at a fixed interest rate into the European money markets. Therefore, we perform two different sets of tests which aim to capture bank-specific economic consequences of the relaxation of fair value rules in the cross-section instead of focusing on market-wide effects. The first set of tests analyses stock price reactions to the IASB approval of the IAS 39 and IFRS 7 reclassification amendments. The second set of tests examines stock price reactions to the eventual reclassification choice at the bank level. We focus our analyses in this section on the potential reclassification benefits that stem from avoiding the violation of regulatory capital restrictions, because other benefits (particularly, avoidance of political costs and of losing depositors) presumably take more time to materialize and are less likely to be unambiguously identified by capital market participants, particularly given the uncertainties in this time of crisis.

We begin the first set of tests by running panel regressions that relate raw bank-specific returns during the period 01 October 2008 31 December 2008 to the DJ STOXX 1800 market index108 and dummy variables that indicate various regulatory

concentrate on the adoption of SFAS 115 which regulates recognition and measurement, Cornet, Rezaee, and Theranian (1996) also include events related to the adoption of SFAS 105 and 107 which regulate footnote disclosures of fair values. Both studies find negative (positive) abnormal returns for time windows around events that increase (decrease) the probability of the adoption of fair value standards. The authors conjecture that investors fear the potential volatility of equity when assets are measured at fair value. In contrast, Lys (1996) argues that the negative reaction is due to regulatory concerns rather than to negative effects of fair value measurement per se.

108 The DJ STOXX Global 1800 Index comprises the largest 600 firms, based on free float market capitalization, from each of Europe, North and South America, and the Asia/Pacific region (e.g., Armstrong, Barth, Jagolinzer, and Riedl, 2010). Since this index also includes banks, we cannot rule

114

events in October 2008 that are related to the reclassification amendments. The coefficient estimates on the event dummies represent abnormal returns (denoted as Abn_ReturnRegEvent below). Next, we focus on the abnormal return on 13/14 October 2008 and analyze its cross-sectional determinants.109 The basic regression specification is as follows:

Abn_ReturnRegEvent = 0 1 Expected Reclassification + 2 Regulatory Capital Restriction (4.2)

Since the reclassification choices at the bank level were unknown when the amendments were announced, we use a dummy variable that indicates whether investors expected a bank to reclassify or not (Expected Reclassification). We use two different

first approach (Perfect Foresight) assumes that investors perfectly predict which banks will use the reclassification option. The second approach (Prediction Model) assumes that investors use the variables identified in the determinants analysis (see table 4.6.5) to assess the likelihood that a bank will use the reclassification option. Specifically, we code banks as expected reclassification (non-reclassification) banks if a probit model with Reclassification (Perfect Foresight) as dependent variable and Regulatory Capital Restriction, Political Incentives, State Ownership, Change in Customer Deposits, Earnings Quality, Income Volatility, %Securities, Exposure to Crisis (Factor), and Log(MCAP/GDP) as independent variables yields a probability of more than 0.5 (less than or equal to 0.5).110 This approach predicts 104 banks to reclassify. 72 of these banks eventually take the reclassification option.

Around the regulatory events, there exists further uncertainty with respect to the future benefits of taking the reclassification option, particularly from avoiding costly regulatory interventions. This uncertainty is captured by the variable Regulatory Capital Restriction.

out that part of the return effect we aim to detect is picked up by the market index control variable. However, this impact is likely to be rather small as the DJ STOXX Global 1800, as of December 2008, contains merely 64 of our sample banks, and works against detecting significant abnormal returns.

109 The IASB approval of the reclassification amendments was announced in the late afternoon (GMT) of 13 October (see table 4.6.6, panel A) when the exchanges in many sample had already closed. We therefore use the cumulative abnormal return on 13/14 October 2008 to ensure that the stock market reaction in all sample countries is captured.

110 We acknowledge that the prediction model also requires perfect foresight of the reclassification choice. However, we think that the probit model provides a useful tool to condense the information that was observable in October 2008 into one single measure.

115

This variable acts as a proxy for the potential savings of regulatory costs and it increases with the probability of regulatory interventions. We use three different specifications for Regulatory Capital Restriction. First, we use the continuous variable as described in table 4.6.2. Second and third, we use dummy variables based on the continuous variable that take a value of one if the difference between an before reclassifications and the minimum capital ratio at country level is less than 2% (61 banks in total; 34 of these banks eventually reclassify) or less than 0% (6 banks in total; 4 of these banks eventually reclassify).111 In order to account for cross-sectional heteroskedasticity and cross-correlation of the residuals, we estimate specification (2) using the weighted portfolio approach by Sefcik and Thompson (1986).

The remaining uncertainty with respect to reclassification choice and effects on the accounts resolves at the reclassification announcement dates. In the second set of test, we analyze stock return around these bank-specific announcements. We use the first reclassification announcement for reclassifying banks and, as benchmark announcements, the first earnings announcement for non-reclassifying banks following the official announcement of the reclassification amendments in October 2008. Since these dates cannot be identified for all sample banks, the analyses are based on a reduced sample of 117 reclassifying and 161 non-reclassifying banks. 14 (67) (36) banks make the reclassification announcement before (during) (after) the respective earnings announcement. 78 (39) banks announce reclassifications in (interim reports prior to) the first annual report following the amendment to IAS 39. The basic regression specification for the short-term analysis is as follows:

Abn_ReturnBankAnn = 0 + 1 Earnings Surprise 2 Reclassification 3 Regulatory Capital Restriction + (4.3)

Abn_ReturnBankAnn is the prediction error from the market model using the DJ STOXX 1800 market index, with interval (-60, -11) and interval (+11, +60) relative to announcement day 0 as estimation window. We follow the trade-to-trade approach of Maynes and Rumsey (1993) to account for thin trading in some of the stocks. Earnings Surprise is an indicator variable that takes a value of one if the earnings number reported

otherwise. Reclassification equals one for banks that announce reclassifications, and zero 111 The two banks that violated the capital restriction and did not use the reclassification option are Gulf

Bank (Kuwait) and Banca Italease (Italy). Both banks merely used the fair value categories in their 2008 financial statements.

116

otherwise. For the Regulatory Capital Restriction variable, we use the same three specifications as in the analysis of stock market reactions to regulatory events. We complement the short-term analysis with long-term analysis of mean market-adjusted returns for up to 120 days before and after the reclassification/earnings announcements. Market-adjusted returns are buy-and-hold bank returns minus buy-and-hold returns on the DJ STOXX 1800 market index.

4.4.4.2 Empirical findings

Table 4.6.6 presents analyses of stock price reactions to the IASB' approval of the reclassification amendments. Panel A reports details on selected regulatory events around the approval in October 2008. Panel B shows mean abnormal returns on these event days

to future reclassifications. Across the five events, we find negative raw returns of -1.69%, but insignificant excess returns once we control for general market movements (not tabulated). Mean abnormal returns for the total sample range from -4.8% (t-statistic -14.53) on 6 October 2008 to +3.1% (t-statistic 8.13) on 9 October 2008. On October

announcements of coordinated government plans to rescue their financial sectors, we measure significant positive abnormal market reactions. Overall, these results confirm that the reclassification amendments were approved in times of extremely volatile stock markets. Panel C presents results of the cross-sectional analysis of abnormal returns on 13/14 October 2008 following the IASB approval of the reclassification amendments. The coefficient estimate on the dummy variable Expected Reclassification is negative throughout all six specifications, but statistically significant in only one specification where the prediction model is used. Since these specifications are based on the strong assumption that the perfect foresight or the prediction model correctly rfindings have to be interpreted with caution.

Our results are less ambiguous with regard to regulatory capital restriction as a cross-sectional determinant of abnormal returns on the day the IASB announced the reclassification amendments. According to the perfect foresight model, the capital market expected 124 banks to reclassify. Four of these banks were expected to violate the regulatory capital restriction (Dummy Cutoff 0% = 1). Our regression analyses show that these banks experience positive abnormal returns on 13/14 October 2008, that are, on average, 5.9% higher than those of the other 120 banks that are expected to reclassify.

117

This effect is statistically significant and even stronger when the prediction model is used. As expected, the effect becomes weaker when the regulatory capital restriction is measured as a 2% cutoff dummy variable and disappears entirely when the continuous variable is applied. These findings suggest that the stock market reacted positively to the reclassification amendments if the reclassification option was expected to be used to safeguard regulatory capital of troubled banks.

Table 4.6.7 presents results from short-term and long-term analyses of stock market reactions to bank-specific announcements of their reclassification choice. Panel A shows that the short-term stock market reactions to bank-specific announcements are generally weaker than the reactions to the IASB announcement of the reclassification amendments. The results of the specifications with Regulatory Capital Restriction (Dummy 0% Cutoff) show that the banks that are expected to violate the regulatory capital restriction and use the reclassification option experience abnormal announcement returns that are 2.6%-2.7% higher on average than those of the other reclassifying banks.112 However, this effect is not statistically significant (t-statistic 1.53 and 1.55, respectively). The earnings surprise variable loads positively as expected. Taken together, these findings suggest that the capital market had largely anticipated the impact of fair value reclassifications on regulatory capital restrictions and impounded this information into

resprices.

Panel B reports mean market-adjusted returns for up to 120 days before and after the reclassification/earnings announcements. The analysis shows stocks of reclassifying banks, on average, performed more poorly before the reclassification than non-reclassifying banks. This finding is line with the results from the determinants analysis (see the Exposure to Crisis variable). Interestingly, stock prices of reclassifying banks also recovered more strongly afterwards. The reclassification effect on regulatory capital does not map into a clear pattern of long-term stock returns. The 60-day window returns again confirm that the reclassification choices were taken in times of extreme volatility. We therefore hesitate to draw a causal link between the reclassification choice and subsequent long-term returns. 112 Untabulated statistics show that the banks that violated the regulatory capital restriction used the

reclassification option to substantially increase their Total Capital. Specifically, for any of these banks, the magnitude of the reclassification effects on Total Capital is higher than the sample median, both in absolute and in relative terms.

118

In summary, our findings are consistent with hypothesis (H1b).

4.4.5 Long-term effects of reclassifications on information asymmetry

4.4.5.1 Research design

In this section, we test hypothesis (H2b). Specifically, we analyze whether stocks of reclassifying IFRS banks experience an increase in information asymmetry in the long run. Following related literature (e.g., Leuz and Verrecchia, 2000; Muller and Riedl, 2002), we use the bid-ask spread as a proxy for information asymmetry. The basic regression specification is as follows:

Log(Bid-Ask Spread) = 0 1 Reclassification 2 Effect on Net Income + 3 Complete Disclosure 4 Effect on Net Income*Complete Disclosure j Controlsj (4.4)

All variables are measured at the firm-quarter level. Bid-Ask Spread is the median quoted spread (i.e. the difference between the closing bid and the closing ask price divided by the midpoint). We use the natural logarithm of the bid-ask spread, because the raw values of this variable are highly skewed (see the descriptive statistics in table 4.6.8, panel A). Reclassification equals one for all reclassification quarters starting with the first quarter during which the respective bank announced IFRS reclassifications, and otherwise equals zero. Effect on Net Income is a dummy variable that takes a value of one if the percentage net income effect of the first reclassification is above the sample median (see table 4.6.2, panel A, for details on this variable), and is zero otherwise. We introduce this variable to account for the assumption that fair value reclassifications need to have a sufficient impact on financial statements in order to affect information asymmetry in capital markets. Complete Disclosure indicates whether a reclassifying bank discloses all six items required by IFRS 7, para. 12A, in the footnotes to its financial statements (see table 4.6.1 and table 4.6.4 for details on this variable).113 Consistent with our second hypothesis, we expect the coefficient estimates on Reclassification and Effect on Net Income 2 1 > 0. In line with

113 39 banks announce reclassifications in interim reports prior to the first annual report following the

amendment to IAS 39. 34 of these banks apply the same IFRS 7 disclosure strategy in the interim reports than in the subsequent annual report. The other 5 banks switch from incomplete disclosure in the interim reports to complete disclosure in the annual report.

119

the mitigating effect of high-quality disclosure on information asymmetry we expect the coefficient estimates on Complete Disclosure and Effect on Net Income * Complete Disclosure to be negative without having priors as to how their values relate to each

3 4 < 0 .

We estimate regression specification (5) using a firm fixed effects model that controls for time trends. The goal of this differences-in-differences approach is to identify a causal relationship between a treatment (reclassification choice) and an endogenous variable (bid-the reclassification option) with its impact on unaffected firms (banks that do not take the reclassification option). To ensure that OLS estimation produces consistent standard errors we use standard errors clustered by firm as suggested by Bertrand, Duflo, and Mullainathan (2004). Since we estimate a firm fixed effects model, our set of control variables is confined to variables that capture firm-specific changes over time. Consistent with finance literature (e.g., Huang and Stoll, 1997), we predict that, ceteris paribus, changes in bid-ask spreads are negatively correlated with changes in share turnover or market capitalization and positively correlated with changes in stock return variability. For all control variables, we use the natural logarithm, because the raw values are highly skewed (see the descriptive statistics in table 4.6.8, panel A).

4.4.5.2 Empirical findings

Table 4.6.8 presents results for the analysis of long-term consequences of fair value reclassifications on bid-ask spreads. Panel A reports descriptive statistics for the dependent and the independent variables. Panel B presents results from multi-period difference-in-differences analyses using the data for all quarters. In panel C, we drop the first two reclassification quarters to examine the long-term impact of the reclassification choice on bid-ask spreads. The sample comprises 124 reclassifying and 178 non-reclassifying banks, which results in a total of 3,467 firm-quarter observations over the period 2007/Q1 to 2009/Q4.

The coefficient estimates on the quarter dummies illustrate that bid-ask spreads increased significantly for non-reclassifying banks in 2008 and moved towards pre-crisis levels at the end of the sample period. This spike in bid-ask spreads remains significant even after including the control variables suggesting that our measure of information asymmetry captures the increased uncertainty during the financial crisis. The coefficient estimates on the reclassification dummy show that reclassifications per se have only a

120

minor impact on bid-ask spreads. However, the results change considerably when we control for the reclassification effect on net income and the quality of disclosures related to the reclassification. In particular, our results suggest that banks that use the reclassification option to inflate their net income experience a significant increase in average bid-ask spreads compared to banks that reclassify with a modest impact on net income (see coefficient estimates on Effect on Net Income in specification (2) and (6)). Further analyses reveal that this increase in information asymmetry is offset if the reclassifications effects are fully disclosed (see coefficient estimates on the interaction term Effect on Net Income * Complete Disclosure in specification (4) and (8)). Translated into economic terms, our results suggest that banks with a high reclassification impact on net income and incomplete disclosure experience an increase in average bid-ask spreads of over 40% relative to non-reclassifying banks (see coefficient estimates on the interaction term Reclassification + Effect on Net Income in specification (4) and (8)). This effect is even stronger (about 60%) in panel C suggesting that the results are not driven by a large but temporary spike in bid-ask spreads around the reclassification announcements. These results are robust to the inclusion of various control variables. Overall, the analyses of the long-term consequences provide evidence for the hypothesis that the reclassification of fair value assets is positively associated with an increase in the information asymmetry component of the bid-ask spread. However, this effect is confined to banks that use the reclassifications to inflate their net income and that do not fully comply with the disclosure requirements of IFRS 7.

4.5 Conclusions and implications

In this study, we examine the economic consequences of the amendments to IAS 39 and IFRS 7. These amendments leave banks reporting under IFRS with the choice to retroactively reclassify financial assets that were previously measured at fair value into categories which require measurement at amortized cost, i.e. to effectively abandon fair value accounting for these assets. Our results suggest that the reclassification option under IFRS produced both short-term benefits and long-term costs. In the short run, the relaxation of IAS 39 fair value rules served as a political means to provide short-term relief for the most troubled banks. To some extent, this objective of granting regulatory forbearance to a few arguably system-relevant economically weak banks has been achieved. Yet it is too early to judge whether the reclassifications were useful to overcome only temporary difficulties or whether they simply delayed a process of market exit because these banks are not economically viable.

121

On the other hand, there is evidence that some banks abuse the reclassification option to decrease transparency of their financial statements more generally by not providing accompanying disclosures required by IFRS 7. Our analyses show that this decrease in transparency coincides with a significant increase in information asymmetry between investors as measured by the bid-ask spread. This finding is important because it supports

al pressure could have come at even higher costs since an EU carve-out of the reclassification rules in IAS 39 had not been accompanied by extensive disclosure requirements. The reliance on footnote disclosure quality, however, can be difficult in an interincentives and the strengths of enforcement institutions differ considerably across countries and non-compliance is still an issue (e.g., Ball, Robin, and Wu, 2003; Barth, Caprio, and Levine, 2001, 2006; Daske, Hail, Leuz, and Verdi, 2009).

Our findings seem to also support arguments that a direct relaxation of capital requirements may have been a more appropriate regulatory measure to address the consequences of the financial crisis rather than a relaxation of fair value accounting (e.g., Laux and Leuz, 2009, 2010). In addition, such a solution would have avoided effects on entities other than banks for which the amendment to IAS 39 introduced the same accounting discretion. At the same time, it is unclear whether a change in capital regulation would have fostered moral hazard on the part of bank managers (Bushman and Landsman, 2010). Other costs might have arisen from the necessity of a more complex and time-consuming coordination process between national legislations, since banking regulations are, unlike the international financial accounting standards, not set by one supra-national body but by local governments.

122

4.6 Tables

4.6.1 Reclassification data and selected variables

No

Yes

No

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tralia

81

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1A

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l Reg

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111

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3033

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100%

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43

36

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Instr

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0.10

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No

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31

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21

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0.08

55%

No

1.0%

313

%-3

0.4%

2.4%

100%

Swed

en4

31

-2

3-

Swed

ish

Fina

nsin

spek

tione

nRe

gula

tion

FFFS

200

7:1

0.08

0%Y

es (2

6.3%

)7.

3%7

57%

-36.

5%2.

8%43

%

Switz

erla

nd6

22

--

11

Fina

ncia

l Mar

ket S

uper

viso

ry A

utho

rity

FIN

MA

Circ

ular

200

8/34

0.08

55%

No

1.4%

013

%-4

0.3%

3.0%

13%

Taiw

an4

54

1-

14

Fina

ncia

l Sup

ervi

sory

Com

mis

sion

Capi

tal A

dequ

acy

Regu

latio

n0.

0855

%N

o9.

0%2

0%-2

9.9%

2.7%

67%

Turk

ey5

8-

17

-8

Bank

ing

Regu

latio

n an

d Su

perv

isio

n A

genc

yRe

gula

tion

OJ 2

6333

/06

0.08

55%

No

13.3

%4

69%

-40.

4%3.

4%31

%

Unite

d A

rab

Emira

tes

78

61

1-

8Ce

ntra

l Ban

kCi

rcul

ar 1

3/19

930.

1055

%N

o21

.7%

047

%-4

.2%

2.5%

0%

Unite

d K

ingd

om4

63

-3

51

Fina

ncia

l Ser

vice

s Aut

horit

yH

andb

ook

GEN

PRU

2.2.

185

0.08

0%Y

es (2

8%)

10.7

%20

650

%-2

0.8%

3.5%

70%

Tota

l / A

vera

ge17

812

452

2745

4282

0.09

61%

6.9%

1931

.4%

-39.

4%1.

8%37

%

Regu

lato

ry A

utho

rity

IIF M

embe

r-sh

ipSt

ock

Retu

rnSt

ock

Retu

rn

Vola

tility

Secu

riti-

zatio

n A

ctiv

ity

Min

imum

Ca

pita

l

AFS

H

airc

uts

(exc

l. Ta

x)

Tax

Ded

uctio

nsSt

ate

Ow

ners

hip

FV in

Po

litic

al

New

s

Not

es:T

hist

able

pres

ents

the

sam

ple

com

posi

tion

byco

untry

and

sele

cted

coun

tryva

riabl

esas

wel

lasc

ount

ryav

erag

esof

sele

cted

bank

varia

bles

.The

full

sam

ple

com

pris

es30

2lis

ted

IFRS

-rep

ortin

gba

nksf

rom

39co

untri

es.T

hesa

mpl

eis

divi

ded

inre

clas

sify

ing

(Yes

)and

non-

recl

assi

fyin

gba

nks

(No

). A

re

clas

sify

ing

bank

isde

fined

asa

bank

that

choo

ses

tore

clas

sify

fair

valu

eas

sets

inac

cord

ance

with

the

amen

dmen

tto

IAS

39in

the

finan

cial

year

2008

.The

colu

mn

Onl

yTr

adin

gre

ports

the

num

bero

fban

ksth

atre

clas

sifie

dex

clus

ivel

ytra

ding

secu

ritie

s.Th

eco

lum

nO

nly

AFS

repo

rtsth

enu

mbe

rof

bank

sth

atre

clas

sifie

dex

clus

ivel

yav

aila

ble

fors

ale

(AFS

)sec

uriti

es.T

heco

lum

nBo

thre

ports

the

num

bero

fban

ksth

atre

clas

sifie

dbo

thtra

ding

and

AFS

secu

ritie

s.Co

mpl

ete

Dis

clos

ure

indi

cate

sw

heth

era

recl

assi

fyin

gba

nkdi

sclo

ses

alls

ixite

ms

requ

ired

byIF

RS7,

para

.12A

,in

the

foot

note

sto

itsfin

anci

alsta

tem

ents.

Regu

lato

ryAu

thor

ityde

note

sth

ein

stitu

tion

whi

chis

resp

onsi

ble

fort

heca

pita

lreg

ulat

ion

ofco

mm

erci

alba

nks

atth

eco

untry

leve

l.Le

galS

ourc

epr

ovid

esth

eso

urce

ofou

rinf

orm

atio

nab

outt

heca

pita

lreg

ulat

ion

varia

bles

.Min

imum

Capi

tal

isth

eto

talc

apita

lrat

io(ti

er1

plus

tier

2)re

quire

dfo

rcom

mer

cial

bank

sby

natio

nalr

egul

ator

s(s

ourc

e:Th

eW

orld

Bank

/ow

nsu

rvey

).AF

SH

airc

uts

isth

epr

opor

tion

ofun

real

ized

AFS

secu

ritie

sga

ins

that

are

dedu

cted

from

the

reva

luat

ion

rese

rves

inth

ede

term

inat

ion

ofto

talr

egul

ator

yca

pita

l.Ta

xD

educ

tions

indi

cate

sw

heth

erfu

ture

tax

char

ges

are

dedu

cted

from

unre

aliz

edga

ins

ofA

FSse

curit

ies

inth

ede

term

inat

ion

ofto

talr

egul

ator

yca

pita

lin

addi

tion

toth

ege

nera

lhai

rcut

(sou

rce:

CEBS

/ow

nsu

rvey

).Co

untry

-spe

cific

tax

rate

sar

eta

ken

from

the

OEC

Dta

xsu

rvey

.Sta

teO

wner

ship

isth

epr

opor

tion

ofa

shar

eshe

ldby

ago

vern

men

tal

insti

tutio

nin

Oct

ober

2008

(sou

rce:

BvD

Bank

Scop

e).T

heta

ble

repo

rtsth

ear

ithm

etic

mea

npe

rcou

ntry

.FV

inPo

litic

alNe

wsis

the

num

bero

ftim

essta

tem

ents

bya

pres

iden

t,pr

ime

min

iste

r,se

cret

ary

offin

ance

,ors

ecre

tary

ofec

onom

icaf

fairs

conc

erni

ngfa

irva

lue

mea

sure

men

t,IA

S39

,and

recl

assi

ficat

ions

wer

eca

ptur

edin

the

new

sbet

wee

nJu

ne20

08an

dO

ctob

er20

09(s

ourc

e:G

oogl

eN

ews)

.IIF

Mem

bers

hip

equa

ls1

ifa

bank

isa

mem

bero

fthe

Inte

rnat

iona

lIns

titut

eof

Fina

nce,

and

0ot

herw

ise

(sou

rce:

IIF).

The

tabl

ere

ports

the

prop

ortio

npe

rcou

ntry

.Sto

ckRe

turn

isa

stock

retu

rnbe

twee

nJa

nuar

yan

dSe

ptem

ber2

008

(sou

rce:

Thom

son

Reut

ers

Dat

astre

am).

Stoc

kRe

turn

Vola

tility

isa

stock

retu

rnvo

latil

itybe

twee

nJa

nuar

yan

dSe

ptem

ber2

008

(sou

rce:

Thom

son

Reut

ers

Dat

astre

am).

Forb

oth

varia

bles

,the

tabl

ere

ports

the

arith

met

icm

ean

perc

ount

ry.S

ecur

itiza

tion

Activ

ity

equa

ls 1

if th

e ba

nk re

ports

eng

agem

ents

in se

curit

izat

ions

in it

s fin

anci

al st

atem

ent a

nd e

qual

s 0 o

ther

wis

e (s

ourc

e: o

wn

data

). Th

e ta

ble

repo

rts th

e pr

opor

tion

per c

ount

ry.

Lega

l Sou

rce

Coun

try

Recl

assi

ficat

ions

Sele

cted

Var

iabl

es

Yes

Capi

tal R

egul

atio

nPo

litic

al In

fluen

ceEf

fect

of F

inan

cial

Cris

is

Tota

lTo

tal

Onl

y Tr

adin

gO

nly

AFS

Both

Com

plet

e D

iscl

osur

e

123

4.6.2 Reclassification effects

Panel A: All Reclassifications

N=124 Mean Std. Dev. P1 Median P99 Mean Std. Dev. P1 Median P99

Net Income 182.960 599.238 -2.666 4.978 3,225.600 43.74% 132.75% -6.45% 3.41% 790.91%

Earnings per Share 0.570 2.866 -0.122 0.011 26.961 26.92% 51.41% -18.14% 3.43% 254.55%

Shareholder's Equity 287.072 976.356 -18.379 8.258 5,000.000 4.88% 15.66% -4.01% 0.78% 88.64%

Return on Equity 0.068 0.438 -0.007 0.004 0.938 47.36% 141.50% -12.38% 3.71% 790.91%

Revaluation Reserve 104.113 702.303 -637.891 0.000 2,130.000 -85.12% 563.35% -2556% 0.00% 110.99%

Tier 1 Capital Ratio 0.174 0.353 -0.124 0.063 1.539 2.05% 4.58% -2.24% 0.65% 18.36%

Total Capital Ratio 0.332 0.889 -0.450 0.102 2.688 19.58% 191.95% -1.96% 0.86% 28.44%

Absolute Effects Relative Effects

Panel B: Trading Reclassifications Only

N=52 Mean Std. Dev. P1 Median P99 Mean Std. Dev. P1 Median P99

Net Income 152.786 534.499 -4.318 8.735 3225.600 67.20% 192.30% -19.75% 7.68% 1109.57%

Earnings per Share 0.262 0.658 -0.122 0.025 3.569 25.77% 45.12% -18.14% 7.32% 214.98%

Shareholder's Equity 132.369 525.930 0.000 0.010 3225.600 0.99% 2.25% 0.00% 0.00% 10.65%

Return on Equity 0.016 0.025 -0.011 0.008 0.150 65.93% 188.76% -19.75% 7.52% 1079.33%

Tier 1 Capital Ratio 0.182 0.288 -0.112 0.106 1.539 1.76% 2.79% -2.24% 1.01% 16.27%

Total Capital Ratio 0.139 0.297 -0.224 0.067 1.603 1.08% 2.20% -1.49% 0.47% 11.88%

Absolute Effects Relative Effects

Panel C: AFS Reclassifications Only

N=27 Mean Std. Dev. P1 Median P99 Mean Std. Dev. P1 Median P99

Revaluation Reserve 83.355 252.927 -14.149 13.877 1,300.000 33.94% 30.95% -14.74% 36.92% 107.26%

Total Capital Ratio 0.331 0.416 -0.087 0.093 1.290 2.58% 3.50% -0.88% 0.90% 11.62%Notes: This table presents the effects of a IAS 39 reclassification choice on its net income and equity capital. The sample of reclassifying bankscomprises 124 IFRS-reporting banks from 39 countries (see table 4.6.1 for details). Absolute effects on net income, equity and revaluationreserve are reported in millions of Euros. Absolute effects on earnings per share are reported in Euros. Absolute effects on return on equity, the tier 1 capitalratio and the total capital (tier 1 plus tier 2) ratio are reported in percentage points. Relative effects are calculated as the absolute effect scaled by the size ofthe respective variable before reclassifications and are reported in percent. Panel A comprises all reclassifying banks. Panel B comprises all banks thatreclassified exclusively trading securities. Panel C comprises all banks that reclassified exclusively available for sale (AFS) securities, i.e. thosereclassifications which did not affect net income and tier 1 capital, but only the revaluation reserve as part of equity and, proportionately (asindicated by AFS Inclusion , see table 4.6.1 for details), tier 2 capital.

Absolute Effects Relative Effects

124

4.6.3 Descriptive statistics

Panel A: Bank VariablesVariables (N = 302) Mean Std. Dev. P1 P25 Median P75 P99

% AFS Assets 0.077 0.081 0.000 0.017 0.052 0.108 0.324% Free Float 55.407 40.018 0.000 9.000 61.000 100.000 100.000

% Securities 0.109 0.096 0.000 0.039 0.083 0.160 0.449

0.014 0.302 -0.493 -0.043 0.001 0.041 0.589Analyst Following 7.040 8.452 0.000 1.000 4.000 11.000 34.000Big 4 Auditor 0.924 0.266 0.000 1.000 1.000 1.000 1.000

Consensus Forecast Target 0.523 0.500 0.000 0.000 1.000 1.000 1.000Earnings Quality 0.510 0.501 0.000 0.000 1.000 1.000 1.000

Exposure to Crisis 0.000 0.646 -1.204 -0.429 -0.031 0.405 1.770

Income Volatility 0.631 0.423 0.063 0.336 0.533 0.796 2.363

No Loss Target 0.149 0.357 0.000 0.000 0.000 0.000 1.000

Political Incentives 0.185 0.389 0.000 0.000 0.000 0.000 1.000

Regulatory AFS Haircut 0.331 0.328 0.000 0.000 0.400 0.550 1.000

Regulatory Capital Restriction -5.554 6.824 -33.139 -6.312 -3.908 -2.409 0.700

State Ownership 0.067 0.158 0.000 0.000 0.003 0.020 0.775Total Assets 127,127 371,986 276 3,130 11,444 47,600 2,105,760

Panel B: Country VariablesVariables (N = 39) Mean Std. Dev. P1 P25 Median P75 P99

CGI Score 0.929 0.731 -0.678 0.453 0.915 1.670 1.970Code Law Country 0.846 0.366 0.000 1.000 1.000 1.000 1.000Emerging Country 0.410 0.498 0.000 0.000 0.000 1.000 1.000

EU Country 0.487 0.506 0.000 0.000 0.000 1.000 1.000

MCAP/GDP 1.206 0.959 0.084 0.540 1.022 1.414 5.005Notes: This table provides descriptive statistics for all variables used in the analyses of the determinants of reclassification choices (table 4.6.5) anddisclosure strategies (table 4.6.4, panel B). The descriptive statistics are based on the full sample of 302 banks (panel A) or 39 countries (panel B),respectively. % Securities (% AFS Assets ) is the proportion of trading assets and AFS assets (AFS assets only) relative to total financial assets. % Free Float is the proportion of total shares issued by a bank that was not closely held at the end of calendar year 2008 (source: Thomson ReutersDatastream). Customer Deposits is a dummy variable for banks that experienced a decrease in customer deposits, scaled by total liabilities,between financial years 2007 and 2008 that is greater than the median decrease (source: BvD Bankscope). Analyst Following is the number ofanalysts that follow the respective bank (source: IBES). Big 4 Auditor is a dummy variable that takes a value of one if a bank is audited by one of thebig 4 auditors, and zero otherwise (source: BvD BankScope). Consensus Forecast Target (Dummy) indicates whether a bank is technically able touse fair value reclassifications to beat consensus forecast. Earnings Quality denotes a average abnormal loan loss provisions sinceIFRS adoption. We use the following regression model to estimate the nondiscretionary portion of the loan loss provision: Loan Loss Provisions /Total Assets = 0 + 1 Loan Loss Reserves t-1 / Total Assets + 2 Net Charge-Offs / Total Assets + 3 Non-Performing Loans / Total Assets + 4

Log(Total Assets) + Exposure to Crisis is the extent to which a bank has been affected by the global financial crisis in 2008. It is the first principalfactor of the following three variables (see table 4.6.1 for details): (1) Stock Return 2008 , (2) Stock Return Volatility 2008 , (3) Securitization Activity . Income Volatility is the standard deviation of a quarterly or half-yearly change in net income, measured in percent, between 2004 and2009 (Source: Worldscope). No Loss Target (Dummy) takes a value of one if net income before reclassifications is smaller than zero and larger thanthe greatest in-sample difference between net income before and net income after reclassifications, i.e. it indicates whether it is technically possiblefor a bank to pass the zero earnings threshold by means of fair value reclassifications. Political Incentives equals one if a bank is a member of theInternational Institute of Finance and if the variable Fair Value in Political News is greater than zero, and zero otherwise (see table 4.6.1 for detailson the underlying variables). Regulatory AFS Haircut is the proportion of unrealized for sale (AFS) securities gain that are not included in thedetermination of regulatory capital (tier 1 plus tier 2). The variable is regulated by national banking supervisors (see table 4.6.1 for a presentation atcountry level) and, when necessary, set at 0% if a bank reports negative revaluation reserves. Regulatory Capital Restriction represents capitalmanagement incentives to reclassify fair value assets, which are defined as the difference between the minimum capital ratio at country level (aspresented in table 4.6.1) and the individual total capital ratio before reclassifications. State Ownership is defined in table 4.6.1. Total Assets is the book value of total assets in million Euros as of financial year 2008 (source: BvD BankScope). CGI Score is a country-specific governance scorefrom Kaufmann, Kraay, and Mastruzzi (2009). MCAP/GDP is the ratio of a stock market capitalization to its Gross Domestic Product(source: The World Bank).

125

4.6.4 Reclassification disclosures

Panel A: Reclassification Disclosures

Amount Reclassified IFRS 7.12A (a) 65 (97%) 54 (95%) 69 (96%)New Category IFRS 7.12A (a) 66 (99%) 57 (100%) 72 (100%)

FV of Reclassified Assets at BS Date IFRS 7.12A (b) 62 (93%) 49 (86%) 66 (92%)

BV of Reclassified Assets at BS Date IFRS 7.12A (b) 62 (93%) not applicable 63 (88%)

Reason for Reclassification IFRS 7.12A (c) 49 (73%) 38 (67%) 59 (82%)

Income / OCI Before Reclassification IFRS 7.12A (d) 44 (66%) 35 (61%) 47 (65%)

Effect of Reclassification on Income / OCI IFRS 7.12A (e) 59 (88%) 50 (88%) 59 (82%)

Effective Interest Rate IFRS 7.12A (f) 38 (57%) 23 (40%) 46 (64%)

Estimated Cash Flow Recovery IFRS 7.12A (f) 33 (49%) 18 (32%) 37 (51%)

Type of Reclassification

HFT2Cost HFT2AFS AFS2CostCategories

Panel B: Determinants of Complete Disclosure

UnivariateAnalyses

0.168 0.344 0.328 0.212

(2.51)** (2.99)*** (2.85)*** (2.57)**

0.160 0.089 0.059 0.166 0.140 -0.054

(2.35)** (0.82) (0.55) (1.53) (1.35) (-0.67)

-0.472 -0.088 -0.104 -0.251 -0.265 -0.120

(-3.46)*** (-0.46) (-0.54) (-1.35) (-1.47) (-0.65)

0.172 0.285 0.301 -0.024 -0.003

(2.02)** (1.64) (1.77)* (-0.19) (-0.02)

-0.199 0.569 0.414 0.350 0.217

(-2.29)** (2.65)*** (1.97)** (1.86)* (1.16)

0.003 0.002 0.002 0.002 0.003 0.002

(4.22)*** (1.42) (1.99)** (1.87)* (2.52)** (1.79)*

0.245 0.222 0.233 0.191 0.204 0.222

(1.50) (1.44) (1.49) (1.13) (1.22) (1.31)

0.012 -0.016 -0.002 -0.015 -0.000 -0.012

(2.72)*** (-2.04)** (-0.24) (-2.00)** (-0.01) (-1.61)

0.002 0.005 0.004 0.003 0.002 0.002

(1.90)* (2.50)** (2.23)** (1.67)* (1.30) (1.43)

0.227 0.152 0.185 0.092 0.128 0.104

(2.65)*** (1.29) (1.74)* (0.78) (1.23) (0.89)

0.098 0.115 0.113 0.098

(4.04)*** (2.56)** (2.57)** (2.20)**Intercept Yes Yes Yes Yes Yes

124 124 124 124 124

0.76 (0.29) 0.77 (0.31) 0.78 (0.36) 0.77 (0.31) 0.80 (0.41)

0.31 (0.16) 0.25 (0.11) 0.26 (0.12) 0.20 (0.08) 0.27 (0.15)

Indepedent Variables

Log(MCAP/GDP)

Dependent Variable: Complete Disclosure

Multivariate Analyses

FV in Political News

Emerging Country

EU Country

Code Law Country

CGI Score

ExpectedSign

+

+

-

+

-

+

Notes: This table presents the results from univariate and multivariate regressions that relate the reclassification choice to various country and bank variables. The dependent variable Reclass_Dummmy is a dummy variable that takes a value of one if a bank reclassifies trading or AFS assets in accordance with IAS 39 in financial year 2008, and zero otherwise (see table 4.6.1). The dependent variable AFSReclass_Dummy is a dummy variable that takes a value of one if a bank reclassifies AFS assets in accordance with IAS 39 in financial year 2008, and zero otherwise (see table 4.6.1). All independent variables are described in table 4.6.1 and table 4.6.3, respectively. The table reports marginal effects at the mean (median) of all continuous (binary) independent variables and z-statistics (in parentheses). The z-statistics are based on robust standard errors. The proportion of correct

**, * indicate statistical significance at the 1%, 5% and 10% levels (two-tailed), respectively.

Number of observations

Correct predictions (scaled)

McFadden's (adjusted) R-squared

+

+

+

+

+

Big 4 Auditor

Analyst Following

Free Float

Earnings Quality

Log(Total Assets)

126

4.6.5 Determinants of reclassification choice

Pane

l B: D

eter

min

ants

of C

ompl

ete

Disc

losu

re

Univ

aria

teA

naly

ses

0.16

80.

344

0.32

80.

212

(2.5

1)**

(2.9

9)**

*(2

.85)

***

(2.5

7)**

0.16

00.

089

0.05

90.

166

0.14

0-0

.054

(2.3

5)**

(0.8

2)(0

.55)

(1.5

3)(1

.35)

(-0.

67)

-0.4

72-0

.088

-0.1

04-0

.251

-0.2

65-0

.120

(-3.

46)*

**(-

0.46

)(-

0.54

)(-

1.35

)(-

1.47

)(-

0.65

)

0.17

20.

285

0.30

1-0

.024

-0.0

03

(2.0

2)**

(1.6

4)(1

.77)

*(-

0.19

)(-

0.02

)

-0.1

990.

569

0.41

40.

350

0.21

7

(-2.

29)*

*(2

.65)

***

(1.9

7)**

(1.8

6)*

(1.1

6)

0.00

30.

002

0.00

20.

002

0.00

30.

002

(4.2

2)**

*(1

.42)

(1.9

9)**

(1.8

7)*

(2.5

2)**

(1.7

9)*

0.24

50.

222

0.23

30.

191

0.20

40.

222

(1.5

0)(1

.44)

(1.4

9)(1

.13)

(1.2

2)(1

.31)

0.01

2-0

.016

-0.0

02-0

.015

-0.0

00-0

.012

(2.7

2)**

*(-

2.04

)**

(-0.

24)

(-2.

00)*

*(-

0.01

)(-

1.61

)

0.00

20.

005

0.00

40.

003

0.00

20.

002

(1.9

0)*

(2.5

0)**

(2.2

3)**

(1.6

7)*

(1.3

0)(1

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0.22

70.

152

0.18

50.

092

0.12

80.

104

(2.6

5)**

*(1

.29)

(1.7

4)*

(0.7

8)(1

.23)

(0.8

9)

0.09

80.

115

0.11

30.

098

(4.0

4)**

*(2

.56)

**(2

.57)

**(2

.20)

**In

terc

ept

Yes

Yes

Yes

Yes

Yes

124

124

124

124

124

0.76

(0.2

9)0.

77 (0

.31)

0.78

(0.3

6)0.

77 (0

.31)

0.80

(0.4

1)

0.31

(0.1

6)0.

25 (0

.11)

0.26

(0.1

2)0.

20 (0

.08)

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(0.1

5)N

otes

: Thi

s tab

le p

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nts t

he re

sults

from

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varia

te a

nd m

ultiv

aria

te re

gres

sion

s tha

t rel

ate

the

recl

assi

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choi

ce to

var

ious

cou

ntry

and

ban

k va

riabl

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he d

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var

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e Re

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umm

my

is a

dum

my

varia

ble

that

take

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ne if

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ank

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ass

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4.6.

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take

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acco

rdan

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ith IA

S 39

in fi

nanc

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ear 2

008,

and

zero

oth

erw

ise

(see

tabl

e 4.

6.1)

. All

inde

pend

ent v

aria

bles

are

des

crib

ed in

tabl

e 4.

6.1

and

tabl

e 4.

6.3,

resp

ectiv

ely.

The

tabl

e re

ports

mar

gina

l effe

cts a

t the

mea

n (m

edia

n) o

f all

cont

inuo

us

(bin

ary)

inde

pend

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aria

bles

and

z-sta

tistic

s (in

par

enth

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). Th

e z-

statis

tics a

re b

ased

on

robu

st sta

ndar

d er

rors

. The

pro

porti

on o

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**, *

indi

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stat

istic

al si

gnifi

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e at

the

1%, 5

% a

nd 1

0% le

vels

(tw

o-ta

iled)

, res

pect

ivel

y.

Num

ber o

f obs

erva

tions

Corr

ect p

redi

ctio

ns (s

cale

d)

McF

adde

n's (a

djus

ted)

R-s

quar

ed

+ + + + +

Big

4 A

udito

r

Ana

lyst

Follo

win

g

Free

Flo

at

Earn

ings

Qua

lity

Log(

Tota

l Ass

ets)

Inde

pede

nt V

aria

bles

Log(

MCA

P/G

DP)

Dep

ende

nt V

aria

ble:

Com

plet

e D

iscl

osur

e

Mul

tivar

iate

Ana

lyse

s

FV in

Pol

itica

l New

s

Emer

ging

Cou

ntry

EU C

ount

ry

Code

Law

Cou

ntry

CGI S

core

Expe

cted

Sign + + - + - +

127

4.6.6 Stock market reactions to regulatory events

Panel A: Events Description

No. Date Description

1 06 Oct 2008(Monday)

European G8 Members meet and explicitly call for a reclassification option (Sarkozy statement in press conference on 04/10/2008) Statement of the Palais de l'Elysee

2 08 Oct 2008(Wednesday)

Following an ECOFIN decision, Commissioner Charlie McCreevy announces in the European Parliament that the EU is prepared to adopt its own EU version of IAS 39 which would include a reclassification option

ECOFIN Press Release (13784/08),European Parliament Speech/08/513

3 09 Oct 2008(Thursday)

IASCF Trustees allow the suspension of the due process for a potential reclassification amendment to IAS 39 Reuters News, 10:59am GMT

4 13 Oct 2008(Monday) IASB adopts reclassification amendments to IAS 39 and IFRS 7 IASB Press Release, 3:42pm GMT

5 15 Oct 2008(Wednesday) EU Commission officially endorses the revised IAS 39 / IFRS 7 EU Press Release (IP/08/1513)

EventSource

Panel B: Univariate Analysis

Yes No Diff. Yes No Diff.

-0.004 -0.004 -0.004 -0.004 -0.005

(-2.17)** (-1.76)* (-2.49)** (-1.35) (-2.76)***

0.416 0.513 0.348 0.611 0.313

(5.59)*** (5.38)*** (5.42)*** (6.10)*** (4.92)***

-0.048 -0.061 -0.040 -0.021 -0.062 -0.041 -0.022

(-14.53)*** (-15.68)*** (-12.74)*** (-11.54)*** (-14.62)*** (-13.83)*** (-10.45)***

-0.030 -0.033 -0.029 -0.004 -0.027 -0.032 0.005

(-9.13)*** (-8.41)*** (-9.27)*** (-2.04)** (-6.29)*** (-10.89)*** (2.62)**

0.031 0.036 0.027 0.009 0.037 0.028 0.009

(8.13)*** (8.12)*** (7.67)*** (4.25)*** (7.47)*** (8.27)*** (3.67)***

0.029 0.026 0.031 -0.005 0.019 0.035 -0.016

(4.68)*** (2.51)** (8.11)*** (-0.57) (2.25)** (6.55)*** (-4.28)***

-0.000 -0.003 0.002 -0.006 0.004 -0.002 0.006

(-0.04) (-0.53) (0.42) (-1.70)* (0.55) (-0.49) (1.81)*

R-squared 0.13 0.15 0.12 0.16 0.12

# Banks 302 124 178 104 198

Event 4 13/14 Oct 2008

Event 5 15 Oct 2008

Expected Reclassification (Perfect Foresight) Expected Reclassification (Prediction Model)

Intercept

Event 3 09 Oct 2008

IndependentVariables

EventWindow

TotalSample

Market Index(DJ STOXX)

Event 1 06 Oct 2008

Event 2 08 Oct 2008

128

Panel C: Cross-Sectional Analysis

0.030 0.030 0.030 0.031 0.032 0.032

(2.57)** (2.63)** (2.71)*** (2.67)*** (2.92)*** (2.93)***

-0.002 -0.009 -0.007

(-0.22) (-1.21) (-0.99)

-0.000 -0.017 -0.014

(-0.00) (-1.85)* (-1.61)

-0.000 -0.000

(-0.54) (-0.76)

0.003 0.002

(0.46) (0.26)

0.026 0.007

(1.59) (0.60)

0.001 0.011 0.033 0.003 0.019 0.082

(0.54) (1.35) (1.23) (1.65) (2.08)** (2.54)**

0.001 0.014 0.059 0.003 0.020 0.090

(0.45) (2.41)** (2.85)*** (1.58) (3.08)*** (3.19)***Notes: This table presents analyses of stock market reactions to selected events around the official announcement of the amendment to IAS 39. Panel Areports details on the regulatory events. Panel B shows results from panel regressions that relate raw bank-specific stock returns during the period 01October 2008 31 December 2008 to the DJ STOXX 1800 market index and event dummy variables. The event window for Event 4 covers two days,because the amendment was announced in the late afternoon of 13 October 2008 (GMT) when the exchanges in many sample countries had already closed.The coefficient estimates on the event dummies represent abnormal returns. We report abnormal returns for the total sample and subsamples based on twodifferent approaches that model expectations with regard to future reclassifications. The first approach (Perfect Foresight ) assumes thatinvestors perfectly predict which banks will use the reclassification option. The second approach (Prediction Model ) assumes that investors use thevariables identified in the determinants analysis (see table 4.6.5) to assess the likelihood that a bank will use the reclassification option. Specifically, wecode banks as expected reclassification (non-reclassification) banks if a probit model with Reclassification (Perfect Foresight) as dependent variable andRegulatory Capital Restriction, Political Incentives, State Ownership, Change in Customer Deposits, Income Volatility, Earnings Quality, %Securities,Exposure to Crisis (Factor), and Log(MCAP/GDP) as independent variables yields a probability of more than 0.5 (less than or equal to 0.5). Thisapproach predicts 104 banks to reclassify. 72 of these banks eventually take the reclassification option. Panel C examines the cross-sectional determinantsof bank-specific abnormal returns following the official announcement of the amendment to IAS 39 (Event 4: 13/14 October 2008). Expected Reclassification (Perfect Foresight) and Expected Reclassification (Prediction Model) are dummy variables that indicate whether a bank is predictedto take the reclassification option. Regulatory Capital Restriction (Continuous) is described in table 4.6.3. Regulatory Capital Restriction (DummyCut-off 2%) and Regulatory Capital Restriction (Dummy Cut-off 0%) are dummy variables that take a value of one if the difference between anindividual total capital ratio before reclassifications and the minimum capital ratio at country level is less than 2% (61 banks in total; 34 of thesebanks eventually reclassify) or less than 0% (6 banks in total; 4 of these banks eventually reclassify). Panel B and C report OLS coefficient estimates and t-statistics (in parentheses). The t-statistics in panel B are based on standard errors that are clustered by date. The coefficient estimates and t-statistics inpanel C are based on the weighted portfolio approach by Sefcik and Thompson (1986). ***, **, * indicate statistical significance at the 1%, 5% and 10%levels, respectively.

Expected Reclassification xRegulatory Capital Restriction

Additional Tests

Regulatory Capital Restriction +Interaction Term

Regulatory Capital Restriction(Continuous)

Regulatory Capital Restriction(Dummy - Cut-off 2%)

Regulatory Capital Restriction(Dummy - Cut-off 0%)

Dependent Variable: Cumulative Abnormal Return on 13/14 October 2008Independent Variables

Intercept

Expected Reclassification(Perfect Foresight)

Expected Reclassification(Prediction Model)

129

4.6.7 Stock market reactions to reclassification announcements

Panel A: Short-Term Analysis

0.002 0.003 0.004 -0.011 -0.008 -0.010

(0.37) (0.50) (0.78) (-1.35) (-0.86) (-1.46)

0.022 0.021 0.022 0.027 0.027 0.028

(1.78)* (1.74)* (1.79)* (1.43) (1.40) (1.53)

-0.014 -0.010 -0.014

(-1.29) (-1.02) (-1.66)*

-0.000 -0.001

(-0.77) (-0.46)

0.010 -0.005

(0.65) (-0.37)

-0.015 0.027

(-1.83)* (1.55)

-0.000 -0.015 0.041

(-0.24) (-0.78) (2.17)**

0.02 0.02 0.02 0.02 0.02 0.02

278 278 278 117 117 117

-0.001 -0.005 0.026

(-0.50) (-0.41) (1.53)Regulatory Capital Restriction +Interaction Term

Additional Tests

Independent Variables

Regulatory Capital Restriction(Dummy - Cutoff 0%)

Reclassification xRegulatory Capital Restriction

R-squared

Observations

Reclassification and Benchmark Announcements

Dependent Variable: Abnormal Return (DJ STOXX) cumulated over Event Days 0 and 1

Reclassification

Regulatory Capital Restriction(Continuous)

Regulatory Capital Restriction(Dummy - Cutoff 2%)

Reclassification Announcements only

Intercept

Earnings Surprise

Panel B: Long-Term Analysis

Yes No Diff. > Median < Median Diff.

-0.087 -0.131 -0.054 -0.077 -0.145 -0.118 -0.027

(-6.01)*** (-5.34)*** (-3.20)*** (-2.57)** (-5.33)*** (-2.88)*** (-0.55)

0.133 0.263 0.036 0.227 0.212 0.314 -0.102

(4.63)*** (4.71)*** (1.43) (3.70)*** (2.47)** (4.37)*** (-0.91)

-0.024 -0.071 0.011 -0.082 -0.091 -0.052 -0.039

(-2.39)** (-4.42)*** (0.90) (-4.09)*** (-4.21)*** (-2.18)** (-1.23)

-0.062 -0.049 -0.071 0.023 -0.080 -0.018 -0.063

(-2.16)** (-0.75) (-4.56)*** (0.34) (-2.47)** (-0.14) (-0.49)

0.029 0.099 -0.022 0.122 0.027 0.170 -0.144

(1.48) (2.73)*** (-1.12) (2.93)*** (0.51) (3.48)*** (-2.00)**

0.105 0.152 0.071 0.082 0.187 0.118 0.069

(7.13)*** (5.79)*** (4.33)*** (2.64)*** (4.71)*** (3.44)*** (1.30)

# Banks 278 117 161 58 59Notes: This table presents results from short- and long-term analyses of stock market reactions to bank-specific reclassification announcements. We usethe first reclassification announcement for reclassifying banks and, as benchmark announcements, the first earnings announcement for non-reclassifyingbanks following the official announcement of the amendment to IAS 39 in October 2008. Since these dates cannot be identified for all sample banks, theanalyses in this table are based on a reduced sample of 117 reclassifying and 161 non-reclassifying banks. 14 (67) (36) banks make the reclassificationannouncement before (during) (after) the respective earnings announcement. 78 (39) banks announce reclassifications in (interim reports prior to) the firstannual report following the amendment to IAS 39. Panel A reports regressions that relate the abnormal announcement return to various cross-sectionaldeterminants. Abnormal return (DJ STOXX) is the prediction error from the market model using the DJ STOXX 1800 market index, with interval (-60, -11) and interval (+11, +60) relative to announcement day 0 as estimation window. We follow the trade-to-trade approach by Maynes and Rumsey (1993)to account for thin trading in some of the stocks. Reclassification equals one for banks that announce reclassifications, and zero otherwise. Earnings Surprise is an indicator variable takes a value of one if the earnings number reported at an earnings announcement is higher than the meanforecast, and zero otherwise. Regulatory Capital Restriction (Continuous) , Regulatory Capital Restriction (Dummy Cut-off 2%), and Regulatory Capital Restriction (Dummy Cut-off 0%) are described in table 4.6.3 and table 4.6.6, respectively. Panel B reports mean market-adjusted returns forup to 120 days before and after the reclassification/earnings announcements. Market-adjusted returns are buy-and-hold bank returns minus buy-and-holdreturns on the DJ STOXX 1800 market index. Mean market-adjusted returns are presented for the total sample and subsamples based on thereclassification choice and the impact of this choice on the tier 1 capital ratio. Both panels report OLS coefficient estimates and t-statistics (inparentheses). The t-statistics are based on robust standard errors. ***, **, * indicate statistical significance at the 1%, 5% and 10% levels, respectively.

(+61, +120)

(-120, -1)

(-120, -61)

(-60, -1)

(+1, +120)

(+1, +60)

Reclassification Effect on Regulatory Capital

Dependent variable: Mean market-adjusted returnTotal

SampleEvent

Window

130

4.6.8 Long-term effects of reclassifications on information asymmetry

Panel A: Descriptive Statistics

Variables # Quarters Mean Std. Dev. P1 P25 Median P75 P99

Bid-Ask Spread 3,467 1.60% 3.34% 0.04% 0.28% 0.66% 1.55% 16.05%

Share Turnover 3,467 0.25% 0.39% 0.00% 0.03% 0.10% 0.32% 1.71%

Market Value (m Euro) 3,467 7,073.28 16,532.68 24.12 327.21 1,354.02 6,117.74 86,607.88

Return Variability 3,467 2.59% 1.57% 0.64% 1.60% 2.26% 3.09% 8.31%

Panel B: All Quarters

(1) (2) (3) (4) (5) (6) (7) (8)

0.077 -0.113 0.143 -0.144 0.042 -0.090 0.142 -0.073

(1.13) (-1.76)* (1.76)* (-1.98)** (0.65) (-1.47) (1.87)* (-1.01)

0.359 0.544 0.250 0.407

(3.43)*** (4.31)*** (2.45)** (3.28)***

-0.210 0.094 -0.319 -0.052

(-1.99)** (0.83) (-3.28)*** (-0.49)

-0.580 -0.501

(-2.98)*** (-2.80)***

-0.189 -0.184 -0.194 -0.187

(-10.40)*** (-10.18)*** (-10.32)*** (-9.95)***

-0.316 -0.313 -0.322 -0.315

(-6.09)*** (-6.18)*** (-6.31)*** (-6.44)***

0.293 0.281 0.305 0.292

(7.40)*** (7.08)*** (7.71)*** (7.44)***

Selected Quarter Dummies

(Benchmark: 2007Q1)

-0.035 -0.035 -0.035 -0.035 0.015 0.012 0.016 0.014

(-1.56) (-1.59) (-1.57) (-1.59) (0.63) (0.54) (0.70) (0.61)

0.031 0.033 0.032 0.035 -0.004 -0.002 -0.003 0.000

(1.12) (1.19) (1.17) (1.27) (-0.17) (-0.07) (-0.13) (0.01)

0.143 0.144 0.144 0.146 0.011 0.015 0.008 0.015

(4.26)*** (4.29)*** (4.28)*** (4.36)*** (0.31) (0.42) (0.24) (0.42)

0.787 0.777 0.785 0.777 0.278 0.285 0.260 0.273

(17.96)*** (17.75)*** (17.94)*** (17.81)*** (4.85)*** (4.97)*** (4.44)*** (4.70)***

0.550 0.554 0.552 0.556 0.183 0.194 0.177 0.191

(10.69)*** (10.76)*** (10.73)*** (10.78)*** (3.43)*** (3.65)*** (3.33)*** (3.61)***

0.297 0.300 0.298 0.303 0.046 0.054 0.043 0.053

(5.43)*** (5.49)*** (5.45)*** (5.52)*** (0.93) (1.08) (0.86) (1.08)

Fixed Effects Firm,Quarter

Firm,Quarter

Firm,Quarter

Firm,Quarter

Firm,Quarter

Firm,Quarter

Firm,Quarter

Firm,Quarter

R-squared 0.91 0.91 0.91 0.91 0.92 0.92 0.92 0.92

# Observations 3,467 3,467 3,467 3,467 3,467 3,467 3,467 3,467

Additional Tests

0.246 0.400 0.160 0.334

(2.53)** (3.50)*** (1.69)* (3.04)***

-0.067 -0.050 -0.177 -0.125

(-0.78) (-0.48) (-2.28)** (-1.39)

-0.086 -0.219

(-0.70) (-2.01)**

Dummy 2009Q2

Dummy 2009Q4

Independent VariablesDependent Variable: Log(Bid-Ask Spread)

Reclassification

Effect on Net Income

Complete Disclosure

Effect on Net Income x Complete Disclosure

Log(Share Turnover)

Log(Market Value)

Log(Return Variability)

Reclassification + Effect on Net Income

Reclassification + Complete Disclosure

Reclassification + Effect on NI +Compl. Discl. + Interaction Term

Dummy 2007Q2

Dummy 2007Q4

Dummy 2008Q2

Dummy 2008Q4

131

Panel C: Without first two reclassification quarters

(1) (2) (3) (4) (5) (6) (7) (8)

0.110 -0.124 0.218 -0.140 0.095 -0.076 0.231 -0.044

(1.34) (-1.58) (2.21)** (-1.61) (1.25) (-1.07) (2.55)** (-0.54)

0.432 0.675 0.316 0.517

(3.51)*** (4.57)*** (2.62)*** (3.57)***

-0.333 0.051 -0.417 -0.097

(-2.71)*** (0.35) (-3.64)*** (-0.73)

-0.727 -0.595

(-3.17)*** (-2.78)***

-0.190 -0.184 -0.195 -0.187

(-10.39)*** (-10.06)*** (-10.45)*** (-9.92)***

-0.328 -0.325 -0.328 -0.318

(-6.03)*** (-6.15)*** (-6.23)*** (-6.34)***

0.288 0.279 0.295 0.286

(7.00)*** (6.79)*** (7.27)*** (7.12)***

Fixed Effects Firm,Quarter

Firm,Quarter

Firm,Quarter

Firm,Quarter

Firm,Quarter

Firm,Quarter

Firm,Quarter

Firm,Quarter

R-squared 0.91 0.91 0.91 0.91 0.92 0.92 0.92 0.93

# Observations 3,220 3,220 3,220 3,220 3,220 3,220 3,220 3,220

Additional Tests

0.308 0.535 0.240 0.473

(2.69)*** (3.95)*** (2.15)** (3.59)***

-0.115 -0.089 -0.186 -0.141

(-1.18) (-0.66) (-2.08)** (-1.20)

-0.141 -0.219

(-1.09) (-1.85)*Notes: This table presents results from regressions that relate bid-ask spreads to the effect of IFRS reclassifications. Panel A reports descriptive statisticsfor the dependent as well as the control variables. All variables are measured at the firm-quarter level. The sample comprises of 124 reclassifying and 178non-reclassifying banks, which results in a total of 3,467 firm-quarter observations over the period 2007/Q1 to 2009/Q4. Panel B present results frommulti-period difference-in-differences analyses using the data for all quarters. In panel C, we drop the first two reclassification quarters to examine thelong-term impact of the reclassification choice on bid-ask spreads. Bid-Ask Spread is the median quoted spread (i.e. the difference between the closing bid and the closing ask price divided by the midpoint, source: Thomson Reuters Datastream). Reclassification equals one for all reclassification quartersstarting with the first quarter during which the respective bank announced IFRS reclassifications, and zero otherwise. Effect on Net Income is a dummyvariable that takes a value of one if the percentage net income effect of the reclassification is above the sample median (see table 4.6.2), and zerootherwise. Complete Disclosure indicates whether a reclassifying bank discloses all six items required by IFRS 7, para. 12A, in the footnotes to itsfinancial statements (see table 4.6.1). Share Turnover is the average percentage trading volume (i.e. trading volume in units divided by the number ofoutstanding shares, source: Thomson Reuters Datastream). Market Value (mEuro) is the median market value of outstanding equity in Million Euros(source: Thomson Reuters Datastream). Return Variability is the standard deviation of daily stock returns (source: Thomson Reuters Datastream). Panel Band C report OLS coefficient estimates and t-statistics (in parentheses). The t-statistics are based on standard errors that are clustered by firm. We use thenatural logarithm of the raw values where indicated in the panels. ***, **, * indicate statistical significance at the 1%, 5% and 10% levels, respectively.

Reclassification

Effect on Net Income

Independent Variables

Complete Disclosure

Reclassification + Complete Disclosure

Reclassification + Effect on NI +Compl. Discl. + Interaction Term

Effect on Net Income x Complete Disclosure

Log(Share Turnover)

Log(Market Value)

Log(Return Variability)

Reclassification + Effect on Net Income

Dependent Variable: Log(Bid-Ask Spread)