Accounting Discretion, Loan Loss Provisioning, and Discipline of Banks’ Risk-Taking

Robert M. Bushman

Kenan-Flagler Business School University of North Carolina-Chapel Hill

Christopher D. Williams Ross School of Business University of Michigan

December 2009

We thank Ryan Ball, Dan Amiram, Dave Larcker, Ed Maydew and workshop participants at Chinese University of Hong Kong, Columbia University, London Business School, MIT, Peking University, University of Missouri, University of Texas at Dallas, Washington University in St. Louis, Yale University, and the 2007 Duke/UNC Fall Camp, for helpful comments. We thank Kenan-Flagler Business School, University of North Carolina at Chapel Hill, for financial support.

Accounting Discretion, Loan Loss Provisioning, and Discipline of Banks’ Risk-Taking

Abstract This paper empirically delineates economic consequences associated with differences in accounting discretion permitted to banks under existing regulatory regimes. Exploiting cross-country variation in loan provisioning practices, we generate country-level measures of observable discretion allowed to banks’ within a given country. We examine implications of discretion for both the informational properties of loan provisions and for bank transparency. First, we investigate the extent to which banks in countries allowing higher discretion use this enhanced flexibility to infuse loan provisioning practices with a more forward looking orientation relative to banks in lower discretion countries. Next, we investigate whether discretion impedes the ability of regulators and outside investors to monitor and discipline bank risk taking. We have three main findings: (1) There is no evidence that banks in high discretion countries impound more forward looking information in loan provisions relative to banks in low discretion countries; (2) Sensitivity of changes in bank leverage to changes in asset volatility is lower in high discretion regimes relative to low discretion regimes; and (3) Banks in high discretion regimes exhibit more risk-shifting relative to banks with less discretion. Our results are consistent with discretion degrading transparency of banks and weakening discipline exerted over bank risk taking. Keywords: Smoothing, Loan Loss Provisions, Discretion, Risk, Banks JEL Classifications: E58, G21, G32, M41

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1. Introduction

The recent financial crisis has energized politicians and regulators to scrutinize financial

accounting standards as never before, creating significant pressure for change. For example,

recent high profile proposals by Financial Stability Forum (2009) and U.S. Treasury (2009) call

for standards setters to re-evaluate the incurred loss model underlying current loan loss

provisioning requirements and consider a range of alternative approaches. A premise of these

proposals is that loan loss accounting should adopt a more forward looking orientation that

allows for recognition of future expected loan losses earlier in the credit cycle, which in turn

would dampen pro-cyclical forces in periods of financial crisis.1 A key aspect of these

alternatives is that, relative to the incurred loss model, they would generally increase the scope

for judgment and discretion in determining loan loss provisions. However, as has long been

recognized (e.g., Watts and Zimmerman (1986)), accounting discretion is a double-edged sword.

On the one hand, increased discretion can facilitate incorporation of more information about

future expected losses into loan provisioning decisions, but on the other hand it increases

potential for opportunistic accounting behavior by bank managers, which may degrade the

transparency of banks and lead to negative consequences.

The main objective of this paper is to empirically delineate significant economic

consequences associated with observable differences in discretion permitted to banks under

existing regulatory regimes. Exploiting significant cross-country variation in observed loan

provisioning practices, we generate country-level measures of the discretion allowed to banks’

within a given country, where discretion is estimated relative to an incurred loss model. Using

1 Financial Stability Forum (2009) defines pro-cyclicality as the dynamic interaction between the financial and the real sectors of the economy that amplify business cycle fluctuations and cause or exacerbate financial instability. See also Dugan (2009).

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these country-level measures of observed discretion, we perform three fundamental analyses

geared towards isolating implications of discretion for both the information properties of loan

provisions and for bank transparency. First, we investigate the extent to which banks in countries

allowing higher discretion use this enhanced flexibility to infuse loan provisioning practices with

a more forward looking orientation relative to banks in lower discretion countries. Next, we

investigate the possibility that discretion imposes costs on the banking system by impeding the

ability of regulators and outside investors to monitor and discipline bank risk taking. We capture

the extent of discipline over bank risk taking using two measures. First, we study the relation

between discretion and the sensitivity of changes in bank capital to changes in the riskiness of a

bank’s assets. Secondly, we examine the relation between discretion and the observed risk-

shifting behavior of banks.2

A fundamental role of financial reporting is to provide credible and relevant firm-specific

information about the financial performance and condition of businesses. Such information is of

central importance for governance of firms and to investors in their resource allocation decisions,

as well as to regulators charged with prudential oversight of financial institutions. Loan loss

provisioning is a key accounting choice that can significantly influence the information

properties of banks’ financial reports with respect to reflecting changes in the fundamental risk

attributes of the underlying loan portfolios.3 Current accounting procedures under both U.S.

GAAP and IFRS utilize an incurred loss framework where a provision for loan losses is

2 As discussed in more detail later in the paper, risk shifting refers to the phenomenon where banks’ equity holders benefit themselves at the expense of deposit insurers by increasing the risk of asset portfolios without adequately increasing bank capital simultaneously. 3A number of papers examine the value relevance of bank loan loss provisions. See for example Beaver et al. (1989), Wahlen (1994), Liu and Ryan (1995), Liu et al. (1997) and Kanagaretnam, Krishnan and Lobo (2009), among others.

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recognized only after loss impairment events have already occurred prior to the financial

reporting date that are likely to result in non-payment of loans in the future. The focus is on

reflecting losses expected to result from events during a given period, while limiting

consideration of expected effects of future events.

An alternative to the incurred loss model posits that regulatory capital should operate as a

buffer against unexpected losses (i.e., large, infrequent occurrences), while loan loss reserves

should deal with expected losses ((Wall and Koch (2000), Basel Committee on Banking

Supervision (1991)). This perspective underlies calls for loan loss accounting to fully incorporate

all future expected losses regardless of whether a loss impairment event has occurred. Such

proposals often introduce elements of earnings smoothing.4 In current deliberations, the FASB

proposes adopting fair value accounting for loans (FASB (2009), while the IASB favors an

expected loss approach where expectations of future losses over the life of a loan are

incorporated ex ante into effective interest rates (IASB (2009). While differing in the details,

such proposed regimes generally allow greater discretion to incorporate a broader range of

available credit information and create an expanded role for managerial judgment in assessing

future expected losses.

But as noted earlier, there are important trade-offs associated with increased discretion,

and any benefits must be weighed against the costs of increased opportunism by managers. To

investigate the economic consequences associated with discretion, we use a large sample of

4 For example, Borio et al. (2001), posits that credit risk builds up in periods of growth and materializes in downturns, and so loan loss reserves should be built up in good times that can be drawn down in bad times. Laeven and Majnoni (2003) also consider benefits of earnings smoothing in which loan loss provisions account for differences between incurred losses today and expected future loan losses. Borio et al. (2001) and Laeven and Majnoni (2003) recognize that such schemes create possibility for opportunistic accounting by bank managers. See Benston and Wall (2005) for discussions of other accounting alternatives.

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banks from 23 countries to estimate two measures of observed discretion allowed to banks within

a given country under the existing regulatory regime. The first is a smoothing measure defined as

the coefficient on earnings in a regression of loan loss provisions on a vector of non-

discretionary provisioning determinates and earnings. A higher coefficient is posited to reflect

more discretion to deviate from the incurred loss model and smooth via the loan loss provision.

The second measure is the incremental explanatory power achieved by adding earnings to a

regression of loan loss provisions on a vector of non-discretionary determinants, where a higher

incremental explanatory power is posited to capture higher levels of discretion.

Using these measures of discretion, we first ask if banks use discretion to more fully

reflect future expected loan losses in current loss provisions. To address this, we test whether the

relation between current loan loss provisions and future changes in non-performing loans

increases with discretion. We find no evidence that banks in high discretion countries employ

loan provisioning practices with a more forward looking orientation relative to banks in low

discretion countries. Failing to find evidence that more discretion is associated with more

forward looking provisioning, we next investigate the possibility that discretion imposes costs on

the banking system by impeding outside discipline over bank risk taking activities.

In our first approach to examining discipline over risk taking activity, we estimate the

impact of increased discretion on the relation between changes in the volatility of bank assets

and changes in bank leverage. This analysis posits that outside discipline imposed by regulators

and investors pressures banks to decrease leverage (increase capital) in response to increases in

risk, and that more intense outside discipline is associated with a higher sensitivity of changes in

leverage to changes in risk. We find that, indicative of discretion dampening disciplinary

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pressure, the sensitivity of changes in bank leverage to changes in asset volatility is lower in high

discretion regimes relative to low discretion regimes.

In our second approach to risk discipline, we investigate the relation between discretion

and bank risk-shifting behavior. Explicit and implicit deposit guarantees create incentives for

banks to shift risk onto the deposit guarantee agency by increasing the risk of assets without

simultaneously increasing capital adequately. Countering such incentives, deposit insurers and

uninsured creditors have incentives to monitor and discipline bank risk taking behavior.

Exploiting Merton’s (1977) characterization of deposit insurance as a put option, and

methodology developed by Duan et al. (1992) and Hovakimian and Kane (2000), we provide

evidence that banks in high discretion regimes exhibit more risk-shifting relative to banks in low

discretion countries. Our results are consistent with discretion being used by bank managers to

degrade the transparency of banks and thereby weaken the ability of regulators and outside

investors to monitor and discipline bank risk taking.

Our paper makes several fundamental contributions to the literature. First, we provide

new evidence on the impact of discretion on information properties of loan provisions and

discipline exerted over bank risk taking activities. This evidence is important in light of the

current push to fundamentally change the accounting for loan provisioning. To the best of our

knowledge, no previous research has investigated connections between the discretionary use of

loan loss provisioning and banks’ risk-taking behavior. There also exists a significant literature

examining the use of discretionary loan loss provisioning to smooth earnings (Moyer, 1990;

Beatty el al., 1995; Collins et al., 1995; Ahmed et al, 1999; Laeven and Majonni, 2003; Liu and

Ryan, 2006). Our paper adds to this literature by documenting significant consequences of

smoothing behavior by exploiting cross-country variation in loan loss provisioning practices.

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Our paper also complements and extends the literature on the role of market discipline in

the regulation of banks (Flannery (1998) and Rochet (2005)) and the growing academic literature

focused on understanding what works best in bank regulation and supervision. Market discipline

seeks to harness market forces in the service of bank regulation and is embedded in the Basel II

Capital Accord.5 We contribute to this literature by demonstrating that the extent of market

discipline over risk taking varies inversely with the extent of discretionary loan provisioning.

That is, while price changes reflect shifts in banks’ perceived value that can trigger outside

scrutiny of banks’ activities, it is plausible that credible, disaggregated information in accounting

reports aids regulators and others in understanding sources of changes in price. This relates to the

distinction between monitoring and influence raised by Bliss and Flannery (2001). We

conjecture that textured accounting information is an important ingrdient for converting the

monitoring role of prices into disciplinary influence. Our results suggest that in regimes with

significant discretion over loan loss provisions, the transparency of banks’ financial reports is

compromised, weakening market discipline.

Finally our paper complements several recent papers that examine various facets of

banks’ accounting discretion. Huizinga and Laeven (2009) examine accounting discretion by

U.S. banks during the 2007-2008 time frame, documenting that banks used discretion to

overstate the value of distressed assets, and that banks with large exposures to mortgage-backed

securities provisioned less for bad loans. Also, Vyas (2009), using a novel measure of financial

reporting transparency, shows that for U.S. financial institutions during the ongoing financial

crisis, exposure to risky assets is reflected in stock prices on a timelier basis for transparent firms

5 The Basel II Capital Accord is based around three complementary pillars Pillar 3 recognizes that market discipline has the potential to reinforce minimum capital standards (Pillar 1) and the supervisory review process (Pillar 2), and so promote safety and soundness in banks and financial systems.

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The rest of the paper is organized as follows. Section 2 puts our paper in context relative

to the extant research on bank accounting and transparency, and also on the role of market

discipline as complementary aspect of bank regulation. Section 3 presents the main empirical

analysis on the relations between country-level provisioning regimes and the discipline of bank

risk-taking. Section 4 concludes.

2. Related Literature

In section 2.1 we discuss the relation of our research to existing literature on loan loss

provisioning and earnings smoothing. In section 2.2 we relate our paper to the literature on role

of market discipline in the regulation of banks and the literature focused on understanding what

works best in bank regulation and supervision. Finally, section 2.3 describes how we draw from

the extant literature in order to carefully control for other aspects of bank regulatory regime as

well as institutional features of the country in general.

2.1 Loan Loss Provisioning and Smoothing

There exists a significant literature examining the use of discretionary loan loss

provisioning to manage earnings, and in particular via earnings smoothing. Using data on U.S.

banks, Greenwald and Sinkey (1988), Collins et al. (1995), Liu and Ryan (2006), and Fonseca

and Gonzalez (2008) document earnings smoothing via loan loss provisions, while Beatty et al.

(1995) and Ahmed et al. (1999) do not. Also, Collins et al. (1995), Beaver and Engel (1996),

and Ahmed et al. (1999) document that discretionary loan-loss provisions are negatively related

to capital, while Beatty et al. (1995) find the opposite result. We extend and complement this

research by documenting significant consequences of discretion by exploiting cross-country

variation in loan loss provisioning practices.

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A long standing debate in the literature concerns whether earnings smoothing increases

the information content of earnings by revealing innate fundamentals or whether it obscures

fundamentals and reduces information in earnings. While some argue that income smoothing

reveals information (e.g., Arya et al., 2003; Chaney and Lewis, 1995; Tucker and Zarowin, 2006;

Trueman and Titman, 1988; Sankar and Subramanyam, 2001; Demski, 1998), others argue that

income smoothing distorts information (e.g., Barth et al., 2007a, 2007b; Francis et al., 2004;

Lang et al., 2003; Leuz et al., 2003). While the existence of earnings smoothing has been

documented, it has proven difficult to empirically distinguish whether smoothing enhances or

obscures information. Our design offers a unique setting in which to address this issue by

investigating whether earnings smoothing at banks is associated with more forward looking

provisioning or whether it imposes costs on the banking system by impeding outside discipline

over bank risk taking activities.

2.2 Market Discipline as a Bank Regulatory Tool

The premise that financial accounting information can play a fundamental role in the

prudential oversight of banks is consistent with the Basel II Capital Accord which posits a

central role for informational transparency in bank regulation in facilitating market discipline.6

While Basel Pillar 3 envisions a range of disclosures that may or may not be part of the formal

financial accounting rules of a given country (BCBS (2001), financial accounting systems form

the foundation of the firm-specific information set available to interested parties outside the firm

6 The Basel II Capital Accord is based around three pillars. Pillar 3 recognizes that market discipline has the potential to reinforce minimum capital standards (Pillar 1) and the supervisory review process (Pillar 2). The Basel Committee on Banking Supervision (BCBS) (2001) notes “Market discipline imposes strong incentives on banks to conduct their business in a safe, sound and efficient manner, including an incentive to maintain a strong capital base as a cushion against potential future losses arising from risk exposures.”

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and are a logical starting point for investigating properties of information important for

addressing moral hazard problems at banks. It is also plausible that the quality of banks’

financial accounting information is correlated with the quality of bank disclosures that fall

outside of a country’s financial accounting rules. Bank transparency can complement prudential

supervision by supporting the financial analysis of banks by private investors which, by

impounding such information into prices, can supplement the information already possessed by

supervisors (Rochet (2005), Hovakimian and Kane (2000), Kane (2004), and Flannery and

Thakor (2006)). Transparency may also enhance ex-ante discipline on bank risk taking activities

as managers will anticipate that informed investors in uninsured liabilities will be more likely to

discern increased risk-taking and respond quickly to greater risks by demanding higher yields on

their investments.7

Barth, Caprio, and Levine (2004) examine regulations on capital adequacy, deposit

insurance system design features, bank supervisory power, regulations fostering information

disclosure and private sector monitoring of banks, and government ownership of banks, among

other factors. Their main results suggest that policies relying on regulatory features that foster

accurate information disclosure, empower private-sector oversight of banks, and foster incentives

for private agents to exert corporate control work best to promote bank development,

performance and stability. Further, Beck, Demirgüç-Kunt, and Levine (2006) find that a

supervisory strategy that empowers private monitoring of banks by forcing banks to disclose

7 Better disclosure may not beneficially impact bank risk taking behavior. For example, Blum (2006) demonstrates that benefits of market discipline via subordinated debt contracts depends on the ability of banks to credibly commit to a given risk level. Cordella and Yeyati (1997) show that public disclosure can serve to reduce bank risk taking, but only to the extent that the bank controls the risk of its portfolio. Plantin, Sapra and Shin (2007) and Allen and Carletti (2008) focus on potential negative effects of mark-to-market accounting on bank soundness.

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accurate information to the private sector, tends to lower the degree to which corruption of bank

officials is an obstacle to firms raising external finance.

Demirgüç-Kunt, Detragiache, and Tressel (2006) study whether compliance with the

Basel Core Principles for Effective Banking Supervision improves bank soundness. They

document that countries which require banks to regularly and accurately report their financial

data to regulators and market participants have sounder banks (measured with Moody’s financial

strength ratings). They note that these findings highlight the importance of transparency in

making supervisory processes effective and strengthening market discipline. Tadesse (2006),

using a range of survey-based metrics find that banking crises are less likely in countries with

greater regulated disclosure and transparency.

Finally, Nier and Baumann (2006) look at the role of bank transparency in providing

incentives for banks to limit their risk. Where we focus on risk shifting behavior, Nier and

Baumann (2006) look at the extent to which higher levels of transparency enhance market

discipline and provide more incentives for banks to limit their risk of default by holding larger

capital buffer. Nier and Baumann’s primary measure of transparency is a bank level index of

disclosure constructed by counting the number of individual disclosures available from

BankScope.

Our paper complements and extends this literature by demonstrating that the extent of

market discipline may depend not only on the existence of informed market prices, but also on

the availability of more textured information provided in banks financial reports that combines

with price triggers to facilitate disciplinary actions by regulators and investors. Our focus on

publicly traded banks implies that all banks in our sample have prices available, and so

differences in market discipline across banks must depend on more than just the existence of

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market prices.8 We conjecture that while prices transmit aggregated information that can trigger

outside scrutiny of the bank’s activities, supplementing this aggregated information with more

textured information amplifies the intensity of disciplinary responses. Stock price changes

reflect shifts in a bank’s perceived value, where credible, disaggregated information in the

bank’s accounting reports can aid regulators and others in understanding the source of changes in

firm value. This conjecture is related to the distinction between monitoring and influence raised

by Bliss and Flannery (2001), where we are contending that textured financial information is a

key element for converting the monitoring role of prices into disciplinary actions by outsiders.

Our results suggest that in regimes where discretion over loan loss provisions allows banks to

smooth earnings, bank transparency is compromised, thus weakening the market-disciplining

role of prices.

It is also important to distinguish our analysis from Laeven and Levine (2009) who focus

on conflicts between bank managers and owners over risk, and document that bank risk is

generally higher in banks that have large owners with substantial cash flow rights. While we do

not have data to control for intricate aspects of bank governance, it also not our objective to

focus on the level of risk that banks take. Instead, we explore whether the sensitivity of bank

leverage (capital) to changes in risk varies with accounting discretion.

2.3 Controlling for other aspects of bank regulatory regime

To isolate the economic consequences of discretion in loan loss provisioning, it is crucial

to control for other key aspects of countries’ bank regulatory regimes as well as other country-

8 As discussed further in section 3.6, we explicitly control for the possibility that market efficiency may vary across countries.

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level institutions. Fueled by recent availability of rich cross-country data on bank regulations and

supervisory practices, the literature discussed in section 2.2 above provides evidence on which of

the many different bank regulations and supervisory practices employed around the world work

best, if at all, to promote banking-sector development, performance, and stability. Barth, Caprio

and Levine (2006) design and implement a survey funded by the World Bank to collect

information on extensive array bank regulations and supervisory practices for many countries.

We rely on Barth, Caprio and Levine (2006) as our source of bank regulatory variables, and

supplement this with variables from other sources. All variables and their sources are described

in detail in Appendix A of the paper.

As discussed above, the Basel II Capital Accord is based around three pillars: (1) Capital

adequacy standards; (2) The supervisory review process; and (3) Market discipline. We follow

Barth, Caprio, and Levine (2006) in controlling for these elements as follows:

Regulations on capital adequacy: CapIndex which is an index constructed by Barth,

Caprio and Levine (2006) to measure the stringency of the capital requirements in each country.

Supervisory power: Official is a measure of the official supervisory power that bank

regulators have over the operations of the bank. This measure is taken from Barth, Caprio and

Levine (2006) and represents an index constructed from answers to individual questions

contained in the survey of bank regulatory practices.

Private-sector monitoring of banks: We include a control variable, Private, developed

by Barth, Caprio, and Levine (2006) which captures the extent to which bank regulations in a

country foster accurate information disclosure, empower private-sector oversight of banks, and

create incentives for private agents to exert corporate control over banks.

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Properties of the general contracting environment: Judicial is an assessment of the

efficiency and integrity of the country’s legal system.

In robustness analyses, we include a wide range of additional control variables. These

include Disclosure, which is a measure of the general disclosure requirements of a country’s

securities regulations; Rights, a measure of the investor protection rights present in the country;

StateBank, to control for the extent of state ownership of banks; Liquidity, which measures the

share turnover of a country’s equity market, a common measure of market development; and

MrktCap, which represents the total market capitalization of a country’s stock market as a

percentage of GDP, again a common measure of market development.

3. Empirical Analysis

This section is organized as follows.

3.1 Sample selection criteria 3.2 Estimating Country-level Discretion in Loan Loss Provisioning Practices 3.3 Discretion and Forwarding-Looking Provisions 3.4 Discretion and Risk-Taking Behavior – Sensitivity of Leverage to Changes in Risk 3.5 Discretion and Risk-Taking Behavior – Risk shifting 3.6 Robustness 3.1 Sample selection criteria

The sample period of our study spans 1995-2006. All bank financial statement data is

taken from Bankscope and all market data is from Datastream. Country-level variables derive

from five different sources; the World Development Indicators Database, Barth et al. (2006),

Demirgüç-Kunt et al. (2005), La Porta et al. (1998), and La Porta et al. (2002). Detailed

information concerning variable construction and data sources are included in Appendix A. To

be included in the sample a bank is required to have all necessary bank-level data spanning a

period of at least three years. We also require that the bank have more than $5 billion in total

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assets. For a country to be included, we require all country-level data to be available. In all

analyses the data is trimmed at the 1 and 99 percentiles. These general requirements yield a

sample of 14,062 potential bank-year observations across 23 different countries. Table 1 Panel A

provides descriptive statistics on the sample.

3.2 Estimating Country-level Discretion in Loan Loss Provisioning Practices

As discussed earlier, the first step in our analysis is to empirically derive estimates of the

amount of discretion allowed to banks in a given country, where discretion is measured relative

to an incurred loss model. We generate two different measures of discretion. The empirical

specification to derive these measures requires that we control for the basic determinants of loan

loss provisions under an incurred loss model. Our basic specification is consistent with extant

banking research in accounting and economics that has previously examined discretionary loan

loss provisioning. The main contribution of our paper is not in the estimation of discretion, but

rather in our investigation of the economic consequences of discretion. Our first measure of

discretion in a country employs the following model which is estimated using OLS:

(1)

LLPitj is the loan loss provision scaled by lagged total loanss for bank i, in country j, at time t.

To control for aspects of the incurred loss model we include both the contemporaneous change in

non-performing loans (∆ ) and net charge-offs (NCO), both scale3d by lagged total loans, to

capture observed changes in portfolio performance and ultimate collectability. We also include

LLPitj 0 1Ebllpitj 2NPLitj 3NCOitj 4 LLRit1, j 5CAPit1, j 6Loansit1, j

7Sizeit1, j 8RLGitj 9%GDPtj

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current period real loan growth (RLG). This variable is included to control for any impact on

loan provisioning related to statistical provisioning applied to an increasing base of

homogeneous loans (Liu and Ryan (2006)), and also to control for increased riskiness of loans.

Existing literature suggests that loan growth represents an important driver of the riskiness of

banks (e.g., Foos et al. (2009), and so we include it to make sure earnings is not simply picking

up risk.9 The percentage change in GDP per capita (%∆ ) is also included to control for

macroeconomic events that may trigger a need to provision. In addition to pure incurred loss

proxies, we also include the level of the loan loss reserve scaled by lagged assets (LLR) and

equity capital to total assets (CAP) at the beginning of the period. Finally, we include the

percent of the bank’s asset in the loan portfolio (Loans) and the size of the bank (Size) to control

for size and asset mix effects.

Our main variable of interest in (1) is earnings before taxes and loan loss provisions

(Ebllp). Under the incurred loss model earnings should not explain contemporaneous

provisioning behavior after controlling for incurred loss proxies and other determinates. Our first

measure of discretion utilizes the estimated coefficient on Ebllp from (1). Prior research (e.g.,

Moyer, 1990; Beatty et al., 1995; Collins et al., 1995; Ahmed et al., 1999; Leaven and Majonni,

2003; Liu and Ryan, 2006) interpret the coefficient on Ebllp as earnings smoothing via the loan

loss provision. We utilize the same interpretation, and presume that such smoothing behavior

represents an important manifestation of discretion allowed to banks under a country’s regulatory

regime.

9 In untabulated results , we also try alternative measures of risk as controls including the volatility of equity and the volatility of assets extracted from an option pricing framework with no qualitative differences in results.

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We begin by first estimating equation (1) using a pooled regression across all banks in

all countries (table 1, panel B). Our objective here is to provide evidence on the general

smoothing behavior of banks in our sample countries. Table 1 reports descriptive statistics of the

sample in Panel A, while Panel B reports the coefficients from the pooled estimation of (1).

Consistent with prior cross-country research by Laeven and Majonni (2003), we find a positive

coefficient on Ebllp indicating that on average banks around the world smooth earnings via the

loan loss provision, and a negative coefficient on the percentage change in GDP, %∆ ,

consistent with banks provisioning less when the business cycle is upward trending. Also, we

see a large, positive coefficient on the contemporaneous change in non-performing loans, ∆ .

To carry out our investigation of the economic consequences of discretion, we need a

measure of discretion at the individual country level. We thus estimate (1) by country where the

coefficient on Ebllp is used as our first country-level measure of managerial discretion, termed

Smoothing. Table 2 reports the descriptive statistics on the country specific estimates of

Smoothing. The mean coefficient estimate is 0.1147 with and standard deviation of 0.2042. Peru

has the highest coefficient (0.7414), whereas Singapore has the lowest (-0.2763). These negative

values raise an interpretation issue, as a large negative could be interpreted as high discretion,

where we are in essence interpreting these negatives as the lowest discretion. To deal with this,

we also use the following measure of discretion which does not rely on the coefficient on

earnings.

Our second measure is the incremental R2 attributed to Ebllp in (1). Our first measure

relies on the sign of the coefficient on Ebllp (i.e., more positive coefficient, more smoothing),

while our second measure is a general measure of how important earnings are in explaining

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variation in provisioning behavior. To obtain the incremental explanatory power of Ebllp we

estimate (1) then estimate (2):

(2)

We then subtract the R2 in (2) from the R2 in (1) and call the resulting measure LLP Opacity,

with higher values interpreted as more discretion in LLP relative to an incurred loss model. Table

1, Panel C reports the results of (1) and (2) and the difference for a pooled regression including

year, bank-type and country fixed effects.

Table 1, Panel C reports that the R2 for (1) is 0.4252 and the R2 from (2) is 0.3642, a

difference (LLP Opacity) equal to 0.0610. To test whether the difference in R2 is significant we

use a Vuong test. Results in Panel C show that the Vuong z-statistic is 6.1498 with a p-value

<0.001. The results in Table 1 Panel C provide evidence that on average Ebllp explains a

significant portion of LLP, with the inclusion of Ebllp increases the R2 17%. We next create a

country-level LLP Opacity measure and report the country-level results in Table 2. The mean

LLP Opacity is 0.0478 with a standard deviation of 0.0978. Similar to Smoothing Peru has the

high LLP Opacity (0.4556), but South Africa has the lowest (0.0000).

Table 2 Panel B reports both the Spearman and Pearson correlations between our

measures of discretion and measures of countries’ bank regulatory regimes and other country-

level institutions. We see that the two measures of provisioning discretion are highly correlated

(0.85- Pearson). It is interesting to note the lack of correlation between discretion and measures

of bank supervisory power (Official), regulations on capital adequacy (CapIndex) and judicial

efficiency of the legal system (Judicial). However, both Smoothing and LLP Opacity are

negatively correlated with Private. Recall Private captures the extent to which bank regulations

LLPitj 0 1NPLitj 2NCOitj 3LLRit1, j 4CAPit1, j 5Loansit1, j

6Sizeit1, j 7RLGitj 8%GDPtj

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in a country foster accurate information disclosure, empower private-sector oversight of banks,

and create incentives for private agents to exert corporate control over banks. These univariate

correlations indicate that the regulatory features captured by Private are associated with less

discretion by banks in loan loss provisioning. It is interesting to note that Barth et al. (2004)

show that Private is associated with better bank development, performance and stability.

3.3 Discretion and Forwarding-Looking Provisions

As discussed in the introduction, Financial Stability Forum (2009), U.S. Treasury (2009)

and others favor increasing the scope for managerial judgment and discretion in determining loan

loss provisions to achieve a more forward looking orientation that allows for recognition of

future expected loan losses earlier in the credit cycle. While we cannot directly investigate the

properties of the specific regimes proposed as such regimes have not yet been widely

implemented, we can empirically examine the extent to which discretion allowed under existing

regulatory regimes is actually used to infuse a forward looking orientation to provisioning. In

this spirit, we test whether the relation between current period loan loss provisions and future

changes in non-performing loans increases as a function of discretion.10 We employ the

following OLS specification for this purpose:

10 Liao and Beatty (2009) also exploit the relation between provisions and future changes in non-performing loans to capture the forward looking orientation of provisioning practices.

LLPitj 0 1LLPREGIMEj *NPLit1, j 2NPLtt1, j 3NPLitj 4NPLit1, j

5NPLit2, j 6LLPREGIMEj 7Ebllpitj 8CAPt1 itj (3)

19

where LLP, ∆ , Ebllp and CAP are as defined above. LLP REGIME is either Smoothing or

LLP Opacity depending on the specification. If discretion is utilized by bank managers to

generate more forward-looking provisions, then we would expect 0. We also control for

other country-level institutional features including Offical, CapIndex, Private and Judicial as

both main effects and interactions along with bank-type and year fixed effects.

Table 3 columns I and II report results using Smoothing as the measure of discretion, and

columns III and IV report the results using LLP Opacity. Columns I and II show that without

controlling for other country-level features the coefficient on is less than zero, but when we

control for other features of the regimes the coefficient is insignificantly different from zero.

This suggests that Smoothing regimes do not promote forward-looking provisioning! Columns

III and IV further confirm this result using LLP Opacity.

Summarizing this analysis, we find that discretion over loan loss provision practices does

not appear to promote forward-looking provisioning. Also, while our two measures of discretion

(Smoothing and LLP Opacity) are positively correlated (table 2, panel B), columns I and III

suggest that there are differences in the measures, and so in what follows we will consider both

measures. Failing to find evidence that more discretion is associated with more forward looking

provisioning, we next investigate the possibility that discretion imposes costs on the banking

system by impeding outside discipline over bank risk taking activities.

3.4 Discretion and Risk-Taking Behavior – Sensitivity of Leverage to Changes in Risk

As discussed in section 2.2, financial accounting information can play a fundamental role

in the prudential oversight of banks by facilitating market discipline. Loan loss provisioning is a

key accounting choice that can significantly influence the information properties of banks’

20

financial reports with respect to reflecting changes in the fundamental risk attributes of the

underlying loan portfolios.

In this section, we take the first of two approaches to investigating the impact of

discretion on the discipline of bank risk taking behavior. This first approach examines whether

the sensitivity of changes in bank leverage (or capital) to changes in risk is impacted by

discretion in loan provisioning. The idea that capital should be an increasing function of risk is a

basic tenet of prudential bank regulation and is reflected in the risk-weighted capital

requirements laid out in the Basel II Accord. To empirically operationalize this construct, we

follow Duan et al. (1992) and model equilibrium relations between increases in risk and changes

in leverage by positing an equilibrium relation that specifies leverage as a linear function of asset

risk. Using this specification, we estimate the sensitivity of leverage to changes in the risk of the

underlying assets, and investigate whether this sensitivity varies with discretion. Specifically we

estimate the following using OLS:

Δ ⁄ Δ (4)

where following Duan et al. (1992), D is the face value of debt, V is the market value of bank

assets, Δ is the change in the volatility of bank assets, and LLP REGIME is either Smoothing

or LLP Opacity depending on the specification. To estimate of V and we focus on publicly

traded banks and exploit the concept that a firm’s equity can be characterized as a call option on

the firm’s assets, where the strike price is the face value of debt. Using measures of face value of

the reported total liabilities (D), the observed market value of equity, and the estimated standard

deviation of stock returns, we obtain values for V and (see Appendix B for further details).

21

Disciplinary pressure should generally result in 0 in (4), where the bank decreases

leverage (increases capital) in response to an increase in risk. To investigate whether discretion

impedes disciplinary responses, we interact Smoothing and LLP Opacity with Δ . A result that

0 implies that discretion over provisioning behavior is associated with leverage being less

sensitive to changes in risk. In estimating (4) we also include other country and bank level

controls as both main effects and interactions.

Table 4 presents the results of the estimation of (4), where for brevity we do not report

the main effects (available upon request). In column I, we document that 0, consistent with

Duan et al. (1992) and the basic intuition that risk discipline should lead banks to decrease

leverage in response to an increase in risk. In table 4, column II we find that the coefficient on

the Smoothing interaction term is 3.18 (p-value < 0.01), consistent with discretion via Smoothing

dampening (making less negative) the sensitivity of leverage to changes in risk.. The same is

found for LLP Opacity in table 4, column III. These findings suggest that when banks are given

discretion over provisioning practices, there is less disciplinary pressure response in leverage

when risk changes.

3.5 Discretion and Risk-Taking Behavior – Risk-Shifting

Deposit insurance provides an explicit or implicit guarantee that in the event of default by

the bank, depositors will receive some proportion of the face value of the deposits.11 Merton

(1977) characterizes deposit insurance as put option written by the deposit insurer to the equity

holders of the bank. The value of this put option in essence represents the fair insurance

11 Under many deposit insurance schemes the full face value (or any fraction of the value) of the debt may not be explicitly guaranteed.

22

premium to the bank for deposit insurance. Our strategy is to exploit the economics of this put

option framework to generate an empirical specification with which to estimate risk-shifting

behavior by banks.

Merton (1977) derives a theoretical pricing model for the deposit insurance put option

that is a non-linear function of the volatility of the bank’s assets and the bank’s leverage. The

existence of this put option creates incentives for banks to shift risk onto the guarantee agency by

increasing the risk of assets without simultaneously increasing capital adequately: Risk-shifting

occurs when banks manage to increase the risk-adjusted cost of deposit insurance that deposit

insurance agencies are unable to pass onto individual banks. Let IPP represent the value of the

put option per dollar of deposits, the volatility of the market value of the bank’s assets,

and ⁄ the leverage of the bank (defined as the face value of debt divided by the market value

of the assets).12 Following Ronn and Verma (1986) and Duan et al. (1992), consider first the

following linear approximation for the value of the deposit put option:

⁄ . . (5)

Note that and in (5) represent the partial derivatives of IPP with respect to volatility and

leverage, respectively. However, deposit insurers and uninsured creditors will generally attempt

to impose discipline on the bank’s risk taking. As a result, banks are not generally unconstrained

in their choice of risk, leverage pairs. To incorporate this disciplinary force into (5), we revisit

the equilibrium relation discussed above in section 3.4 that specifies leverage as a linear function

of asset volatility (i.e., equation (4)). That is, consider the relation:

12 Merton (1977) derives the comparative static results that 0 and ⁄

0.

23

⁄ , (6)

where, 0 in (6) represents the natural equilibrium relation between risk and leverage

(capital). We embed the disciplinary force from (6) in (5) by substituting the right hand side of

(6) into (5) for D/V and simplify, yielding

, (7)

where ⁄

. The coefficient captures the net effect of the

struggle between risk-shifting banks and outside disciplining forces. The first term in (4), ,

captures the bank’s incentive to increase risk, while the second term, ⁄

, is generally

negative and captures the offsetting impact of the disciplinary response to increased risk via .

This second term is generally negative as is expected to be negative and ⁄

0. The overall

interpretation is that 0 is consistent with observed risk-shifting as the disciplining effect

does not completely neutralize incentives to increase risk. The economic intuition behind the

interpretation of as observed risk-shifting is that if banks find risk-shifting behavior beneficial

(i.e. profit maximizing) then they would manage their overall risk levels in such a way that

would increase the actuarially fair value of their insurance. If banks do not find risk-shifting

behavior to be advantageous, they would have no incentive to manage their risk in such a way

because any increases in the risk profile would be borne by the equity holders of the bank.

24

Following Duan et al. (1992), Hovakimian and Kane (2000), and Hovakimian, Kane and

Laeven (2003), we estimate variants of (7) in changes to examine the relation between discretion

and risk shifting. In particular, we estimate the following:

(8)

where IPP is the change in the fair deposit insurance premium (see Appendix A for calculation)

and other variables are defined above. The coefficient captures the impact of discretion on

risk shifting, where >0 would be consistent with higher discretion increasing risk shifting.

In Table 5, panel B, column I reports the estimation of risk shifting forces in general,

documenting that 0. That is on average, banks’ risk shifting incentives dominate the

disciplinary pressure imposed on them by regulators and investors. We next examine whether

Smoothing and LLP Opacity exacerbate observed risk shifting. Columns II and III of Table 5

Panel B, document a coefficient of 0.2458 (p-value < 0.01) for the interaction with Smoothing,

and a coefficient of 0.3533 (p-value < 0.01) for the interaction with LLP Opacity. Taken together

the results show that in regimes where banks are given more discretion over the loan loss

provision there is more observed risk shifting.

Incentives to risk shift should generally increase with declining performance, of the bank

(e.g., Eisdorfer (2008), Loktionov (2009)), implying that the effects documented in Table 5

should be more pronounced in poor performing banks. To test this conjecture we first rank our

banks by return on equity (ROE) into quintiles and then take the top quintile as good performers

and the bottom as poor performers. We predict that we should observe risk shifting in low ROE

firms; we then interact country-level discretionary provision measure and expect that the opacity

magnify the effect in the low ROE firms. Table 6 panels A and B report the results.

IPP 0 1 v 2 v * LLPREGIME 3LLPREGIME

25

Focusing first on Panel A, the first two columns shows that for poor performers, the

coefficient on the change in risk is 0.1646 (p-value < 0.01), indicative of poor performers having

strong incentives to risk shift. In contrast, for the high ROE group, the coefficient on the change

in risk is insignificantly different from zero. Turning now to impact of discretion, and focusing

our discussion on the Smoothing results in panel A (LLP Opacity provides similar results in

panel B), we find for the low ROE group the coefficient on the Smoothing interaction is positive

(0.4553) and significant (p-value < 0.01), whereas for the high ROE group the coefficient is

insignificant (0.0960, p-value > 0.10). These results suggest that in time of poor performance

banks have the incentive to risk shift and moreover, discretion over loan provisioning

exacerbates the effect.

Overall, the results of sections 3.4 and 3.5 are consistent with discretion resulting in

lower bank transparency which in turn weakens the ability of regulators and outside investors to

monitor and discipline bank risk taking

3.6 Robustness

We first address basic issues of correlated omitted variables. We rerun our risk-shifting

specification from tables 5, but now include a wide range of additional variables that might affect

risk shifting. All variables are defined in detail in Appendix A. First we include the well known

measure of the general securities market disclosure in a country from LaPorta et al. (2006)

(Disclosure). We also control for whether the bank is state owned (StateBank) as such banks may

have differing incentives. To control for cross-country differences in shareholder rights,

following LaPorta et al. (1998) we include a proxy for shareholder rights (Rights). Because the

risk shifting analyses relies on market prices, we control for development of the equity markets

in a country by including the country’s market liquidity (Liquidity) (LaPorta et al., 2006), and

26

the country’s total stock market capitalization (MrktCap). Table 7, Panel A and B show that the

our results are robust to the inclusion of these variables.

Another important issue revolves around the fact that we use stock prices to extract our

estimates of the market value of assets, V, and risk, Δ . As noted by Griffen et al. (2007), there

can be differences across countries in market efficiency. To the extent that market efficiency

differs across countries, our estimates of V and Δ could embed measurement error that varies

with market efficiency, and this measure error could be correlated with our estimates of

discretion, Smoothing and LLP Opacity. Following Griffen et al. (2007), we split countries into

developed and undeveloped markets, where the variable EfficientMrkt is set equal to 1 if the

market is developed (i.e., efficient) and 0 otherwise. Table 8 reports the results for the

regressions. The EfficientMrkt interaction does not load, and the Smoothing interaction is 0.2815

(p-value < 0.01). That is, our results do not appear to be explained by measurement error

resulting from cross-country differences in market efficiency.

Finally, we run a large array of additional robustness tests. First, we verify that our results

are not attributable to any one country. We re-run all analyses sequentially excluding a different

county each time, and find that no one country drives the results presented in Tables 3-8. In

particular, our results are robust to excluding Spain, which at some points during our sample

period employed a dynamic provisioning regime for its banks (e.g., Fernández de Lis et al.

(2001)). Another concern is simultaneity bias in the leverage regressions. Following prior

research we test for this bias using a Hausman Test and, consistent with prior literature, find no

evidence of simultaneity present in the analysis.

27

7. Summary and Conclusions

This paper empirically delineates economic consequences associated with differences in

accounting discretion permitted to banks under existing regulatory regimes. Exploiting cross-

country variation in loan provisioning practices, we generate country-level measures of

discretion allowed to banks’ within a given country. We examine implications of discretion for

both the information properties of loan provisions and for bank transparency.

First, we investigate the extent to which banks in countries allowing higher discretion use

this enhanced flexibility to infuse loan provisioning practices with a more forward looking

orientation relative to banks in lower discretion countries. Next, we investigate whether

discretion impedes the ability of regulators and outside investors to monitor and discipline bank

risk taking.

We have three main findings: (1) There is no evidence that banks in high discretion

countries impound more forward looking information in loan provisions relative to banks in low

discretion countries; (2) Sensitivity of changes in bank leverage to changes in asset volatility is

lower in high discretion regimes relative to low discretion regimes; and (3) Banks in high

discretion regimes exhibit more risk-shifting relative to banks with less discretion. Our results

are consistent with discretion degrading transparency of banks and weakening discipline exerted

over bank risk taking.

Overall, this evidence is consistent with the idea that discretion through loan loss

provisioning degrades the transparency of banks and thereby weakens the ability of regulators

and outside investors to monitor and discipline bank risk taking. The impact of discretion persists

after controlling for key elements of a country’s financial development, bank regulatory

practices, and bank level characteristics. This evidence does not however imply that forward-

28

looking provisioning schemes, as put forth in recent proposals, are necessarily doomed to failure.

We have only examined the loan loss provisioning regimes in place during our sample period,

and it is possible that carefully designed forward-looking regimes can mitigate issues of

procyclicality without compromising bank transparency. What our results do show is that great

care must be exercised with respect to allowing more discretion into loan provisioning, and that

perceived gains to forward-looking provisioning regimes must be weighed against potential

losses in bank transparency due to opportunistic accounting choices.

29

Appendix A

Variable Description Reference/Source Smoothing Defined as the coefficient on Ebllp from model (1).

LLP Opacity Defined as the R2 from (1) minus the R2 from (2).

LLP The reported loan loss provision on the income statement the end of the period scaled by lagged total loans outstanding.

Bankscope

Ebllp Earnings before taxes and loan loss provisions scaled by lagged total loans

Bankscope

NPL The change in non-performing loans over the reporting period scaled by total loans outstanding.

Bankscope

NCO Net charge-offs as of the end of the reporting period scaled by lagged loans outstanding.

Bankscope

LLR The lagged level of the loan loss reserve scaled by lagged total loans outstanding.

Bankscope

CAP Book value of equity reported at the end of the period scaled by end of period total assets.

Bankscope

Loans Total loans outstanding at the end of the period scaled by total assets.

Bankscope

Size Natural logarithm of total assets.

Bankscope

RLG The change in loans outstanding over the reporting period deflated by the CPI and scaled by lagged loans outstanding.

Bankscope/World Development Indicators

(WDI) %GDP Percentage change in GDP per capita.

WDI

Official An index computed from answers to the following

questions: (a) Does the supervisory agency have the rights to met with external auditors to discuss their reports without the approval of the bank?; (b) Are auditors required by law to communicate directly to the supervisory agency and presumed involvement of bank directors or senior managers in illicit activities, fraud, or insider abuse?; (c) Are offbalance sheet items disclosed to the supervisors?; Can supervisors: (d) take legal action against external auditors for negligence?; (e) force a bank to change its internal organizational structure?; (f) order a bank’s directors or management to constitute provisions to cover actual or potential losses?; (g) suspend the directors’ decision to distribute bonuses?; (h) suspend the director’s

Barth, Caprio and Levine (2006, 2007)

30

decision to distribute management fees?; (i) Who can legally declare – such that this declaration supersedes some of the rights of shareholders – that a bank is insolvent?; (j) According to the Banking Law, who has authority to intervene – that is, suspend some or all ownership rights – a problem bank?; Regarding bank restructuring and reorganization, can the supervisory agency or any other government agency: (k) supersede shareholder rights?; (l) remove or replace management?; and (m) remove and replace directors?

CapIndex A composite measure that captures both the amount of

capital and verifiable sources that a bank is required to posses. The index is created from a answers to the following questions as of 2003: 1) Are the sources of funds to be used as capital verified by the regulatory/supervisory authorities? 20 Can the initial disbursement of subsequent injections of capital be done with assets other than cash or government securities? 3) Can initial disbursement of capital be done with borrowed funds? 4) is the minimum capital-asset ratio risk-weighted in line with the Basel guidelines? 5) Does the minimum ratio vary as a function of market risk? 6) Are market value of loan losses not realized in accounting books deducted? 7) Are unrealized losses in securities portfolios deducted? 8) Are Unrealized foreign exchange losses deducted?

Barth, Caprio and Levine (2006, 2007)

Private A composite index comprised of answers to the following

questions: 1) is there an explicit deposit insurance protection scheme? 2) Does accrued, though unpaid interest/principal enter the income statement while the loan is still non-performing? 3) Are financial institutions required to produce consolidated accounts covering all bank and any non-financial subsidiaries? 4) Must banks disclose their risk management procedures to the public? 5) Are all of the top ten banks in the country rated by international credit rating agencies?

Barth, Caprio and Levine (2006, 2007)

Judicial Assessment of the “efficiency and integrity of the legal

environment as it affect business, particularly foreign firms” produced by the country-risk rating agency Business International Corporation. Average between 1980 and 1993. Scale between 0 to 10, with lower scores equal to lower efficiency levels.

LaPorta, Lopez-de-Silanes, Shleifer and

Vishny (1998)

v The change in the underlying risk of the assets, see

Appendix B for computation details. Ronn and Verma

(1986)

DV

The change in the face value of debt as of the end of the fiscal period divided by the market value of the assets (see Appendix B for computation details).

Ronn and Verma (1986)

ROE Return on equity defined as earnings before taxes scaled by

owner’s equity. Bankscope

31

Disclosure A measure of disclosure created from components of the general securities law disclosure requirements.

LaPorta, Lopez-de-Silanes, and Shleifer

(2006) (LLS) StateBank Share of the assets of the top 10 banks in a given country

owned by the government of that country. LaPorta, Lopez-de-Silanes and Shleifer

(2002) Rights A summary measure of shareholder rights in a country,

measured as the number of important shareholder rights that exist in the country’s legal code.

LaPorta, Lopez-de-Silianes, Shleifer and

Vishny (1998) Liquidity The average total value of stocks traded as a percentage of

GDP for the period 1996 to 2000. WDI/LLS

MrktCap The countries total market capitalization divided by GDP WDI EfficientMrkt And indicator variable equal to 1 if the market is developed

and 0 otherwise. Griffin, Kelly, and

Nadrin (2007)

32

Appendix B

Estimating V, and IPP:

To estimate V-the market value of assets, -the instantaneous standard deviation of the rate of return on the value of the bank’s assets, and IPP-the fair value of the deposit insurance put-option per dollar of deposit. To estimate each of these variables we follow Ronn and Varma (1986). We first obtain value of V and by solving two simultaneous equations. The solutions from these two equations are then used to calculate IPP. We like prior research make the following assumptions: first, deposits equal the total liabilities of the bank. Second, asset values follow a geometric Brownian motion. Third, because deposits are of the demand type we assume the time to maturity is the time to the next audit this way the guarantor can treat the deposits as if they were term and interest bearing. The first equation states as a function of market value of equity (E), V, and the instantaneous standard deviation of return on equity over the prior twelve-month period(E ) :

v

EE

VN(x) (a) where

x

ln(V D) v2 T 2

v T N( ) is the cumulative density of a standard normal random variable. is the forbearance parameter to capture regulators desire to stay the exercise of the option in hopes of a recovery in the bank. Following prior research we set this parameter equal to 0.97, which allows the asset value to deteriorate to 97 percent of the debt value before the option is called. T is the unit of time until the next audit, which is set equal to 1. The second equation is the option formulation for E. Following Merton (1977) and Ronn and Verma (1986) we model the market value of the bank’s equity as:

E VN (x) DN (x v T ) (b) where all variables are defined previously. After simultaneously solving (a) and (b) for V and , we then solve for Merton’s (1977) fair value of the deposit insurance put-option, IPP:

IPP N(y V T ) (1 )n V

D

N(y) (c)

33

where

y

ln D V (1 )n v2 T 2

v T and is the dividend per dollar of value of the assets, paid n time per period. The resulting IPP is the deposit insurance put-option (or actuarial fair insurance premium) per dollar of deposits.

34

Table 1 International Examination of Smoothing by Banks

OLS regression of loan loss provisions (LLP) on earnings before provisions and tax (Ebllp), change in non-performing loans ( ), net charge-offs (NCO), beginning period loan loss reserves (LLR), capital (CAP), loans to assets (Loans), the natural logarithm of the bank’s assets (Size), real growth in loan portfolio (RLG) and percentage change in GDP per capita ( ). Bank specific variables are trimmed at the 1 and 99 percentiles. Standard errors (reported) are clustered at the bank level. Country, bank type and year fixed effects are included. Data range 1995-2006. Panel A. Descriptive Statistics

Variable Mean Median StdDev LLP 0.0082 0.0042 0.0196 Ebllp 0.0346 0.0262 0.0826

-0.0008 -0.0003 0.0443 NCO 0.0078 0.0019 0.0589 LLR 0.2845 0.0159 0.0482 CAP 0.0899 0.0799 0.0646 Loans 0.6166 0.6322 0.1539 Size 7.9367 7.7619 1.8017 RLG 0.0787 0.0536 0.2946

1.8471 2.2408 2.2608

Panel B. OLS Regression – Smoothing via LLP

Variable Prediction Dependent Variable: LLP

Ebllp + 0.0786*** (0.023)

0.1104*** (0.021)

NCO -0.0495*** (0.013)

LLR 0.0621** (0.026)

CAP -0.0044 (0.010)

Loans 0.0065*** (0.002)

Size 0.0001 (0.001)

RLG 0.0090** (0.005)

-0.0018*** (0.002)

R2 0.4252 Observations 14,062 ***, **, * indicates significance at the 0.01, 0.05 and 0.10 level respectively. Panel C. Ebllp Incremental R2-Vuong Test Model R2 Z-Statistic P-Value Including Ebllp 0.4252 Excluding Ebllp 0.3642 Difference 0.0610*** 6.1498 <0.001

NPL

GDP

NPL

%GDP

NPL

%GDP

35

Table 2

Country-Level Statistics Panel A. Descriptive Statistics

Country Smoothing LLP

Opacity Official CapIndex Private Judicial Argentina 0.0540 0.0239 9.5 7 2.0 6.00 Australia 0.0858 0.0211 11.0 7 4.0 10.00 Canada 0.1193 0.0122 10.5 4 3.0 9.25 Chile 0.3405 0.1421 11.0 6 1.9 7.25 Hong Kong 0.2213 0.0770 11.0 7 4.0 10.00 India 0.4837 0.1420 10.0 8 0.3 8.00 Ireland 0.1830 0.0078 13.0 4 3.0 8.75 Israel -0.1137 0.0203 8.0 7 3.5 10.00 Japan 0.1865 0.0245 12.0 6 3.0 10.00 Mexico -0.0096 0.0021 11.5 8 3.0 6.00 Norway 0.1540 0.0241 9.0 7 3.0 10.00 Pakistan 0.0747 0.0115 13.0 7 2.4 5.00 Peru 0.7414 0.4556 12.0 6 1.4 6.75 Philippines 0.2137 0.0701 11.0 5 2.9 4.75 Portugal 0.0176 0.0045 14.0 7 2.8 5.50 Singapore -0.2763 0.0032 12.5 8 4.0 10.00 South Africa 0.0056 0.0000 9.0 7 3.5 6.00 Spain 0.0829 0.0315 8.5 10 2.0 6.25 Thailand -0.0297 0.0020 9.0 5 3.0 3.25 Turkey 0.0764 0.0206 14.0 6 2.9 4.00 U.K. 0.0011 0.0001 11.5 6 3.0 10.00 U.S.A. 0.0218 0.0042 13.0 6 2.0 10.00 Zimbabwe 0.0036 0.0001 14.0 5 3.0 7.50 Panel B. Correlation Matrix (Pearson-Lower/Spearman-Upper) Smoothing LLP Opacity Official CapIndex Private Judicial Smoothing 0.8449*** -0.0199 -0.1777 -0.4270** 0.0601

LLP Opacity 0.8575*** -0.2550 0.1312 -0.4311*** 0.0521

Official 0.0046 -0.0018 -0.2901 -0.1155 -0.0793

CapIndex -0.1336 -0.0120 -0.3231 0.0225 0.0942

Private -0.6401** -0.5199** 0.0335 -0.1331 0.4237**

Judicial -0.0583 -0.0643 -0.0594 0.0097 0.2617

***, **, * indicates significance at the 0.01, 0.05 and 0.10 level respectively.

36

Table 3 Smoothing, LLP Opacity and Future Charge-offs

OLS regression where LLPt (loan loss provision) is regressed on (where NPL is

non-performing loans), CAP (beginning of the period capital ratio) and Ebllp (earnings before taxes and loan loss provisions). Smoothing is the country-level coefficient from an OLS regression of loan loss provisions on earnings before provisions and tax (Ebllp). LLP Opacity is the incremental adjusted R2 attributed to Ebllp in the country-level smoothing regression. CapIndex, Private, Official, Judical and GDP are country-level control variables (see Appendix A). Bank variables are trimmed at the 1 and 99 percentiles. For brevity main effects are included in regressions but not reported. Standard errors (reported) are clustered at the bank level. Both bank type and year fixed effects are included. Data range 1995-2006. Dependent Variable: LLPt

Variables I II III IV NPLt1 * Smoothing -0.4855** -0.2270 (0.18) (0.14)

NPLt1 * LLPOpacity -1.0785 -0.0469 (0.79) (0.56)

NPLt1 -0.0137 0.4224 -0.0464 0.3456 (0.03) (0.26) (0.03) (0.31)

NPLt 0.1122*** 0.1146*** 0.1094*** 0.1150*** (0.02) (0.02) (0.02) (0.02)

NPLt1 0.0351*** 0.0360*** 0.0366*** 0.0372*** (0.01) (0.01) (0.01) (0.01)

NPLt2 0.0207 0.0215 0.0222* 0.0238* (0.02) (0.02) (0.01) (0.02)

NPLt1 *Offical -0.0226* -0.0245* (0.01) (0.02)

NPLt1 *CapIndex -0.0337** -0.0296 (0.01) (0.02)

NPLt1 * Pr ivate 0.0294 0.0622 (0.04) (0.04)

NPLt1 * Judicial -0.0105 -0.0160 (0.01) (0.01)

Ebllpt 0.1424*** 0.1380*** 0.1398*** 0.1335*** (0.02) (0.03) (0.02) (0.02)

CAPt1 0.0001 0.0001* 0.0001** 0.0001*** (0.01) (0.00) (0.00) (0.00) R2 0.3246 0.3334 0.3081 0.3253 Observations 5,032 5,032 5,032 5,032 ***, **, * indicates significance at the 0.01, 0.05 and 0.10 level respectively.

NPLt 2

,NPLt 1

,NPLt, NPL

t 1

37

Table 4 Smoothing, LLP Opacity and the Sensitivity of Capital to Risk

OLS regression results of changes in debt-to-assets ( ) on changes in asset risk ( ) interacted with country-

level institutional features. is the face value of debt divided by the market value of assets and is the

change in the underlying assets of the firm (see Appendix B for details). Smoothing is the country-level coefficient from an OLS regression of loan loss provisions on earnings before provisions and tax (Ebllp). LLP Opacity is the incremental adjusted R2 attributed to Ebllp in the country-level smoothing regression. CapIndex, Private, Official, Judical and GDP are country-level control variables (see Appendix A). ROE is bank level return on equity and Size is the natural logarithm of the bank’s assets. Bank specific variables are trimmed at the 1 and 99 percentiles. For brevity main effects are included in regressions but not reported. Standard errors (reported) are clustered at the bank level. Both bank type and year fixed effects are included. Data range 1995-2006. Panel A. Descriptive Statistics

Variable Mean Median StdDev -0.0047 -0.0012 0.1421

-0.0026 -0.0019 0.2625 SIZE 7.9755 7.7313 1.8162 ROE 0.1204 0.1273 0.1729 Panel B. OLS Regressions – Capital Sensitivity

Dependent Variable:

Variables Predictions I II III

*Smoothing + 3.1788 *** (0.376)

*LLP Opacity + 4.5303*** (0.759)

*Official 0.0260 0.0114 (0.071) (0.079)

*CapIndex 0.1495 0.1668 (0.130) (0.143)

*Private 0.4726** 0.3504 (0.191) (0.237)

*Judicial -0.2609*** -0.2462*** (0.032) (0.035)

*Size -0.1041** -0.1128** (0.048) (0.051)

*ROE -0.1651 -0.1203 (0.159) (0.155)

*GDP 0.0382 -0.0488 (0.029) (0.035)

-1.2503*** -1.7022 1.1614 (0.254) (1.581) (1.669)

R2 0.4517 0.6072 0.5915 Observations 3,949 3,061 3,061 ***, **, * indicates significance at the 0.01, 0.05 and 0.10 level respectively.

D V V

D V V

V

D V

D V

V

V

V

V

V

V

V

V

V

V

38

Table 5 Smoothing, LLP Opacity and Risk-Shifting

OLS regression results of changes in IPP ( ) on changes in asset risk ( ) interacted with country-level

institutional features. Following Merton (1977) is the fair value of the deposit insurance premium and is

the change in the underlying assets of the firm (see Appendix B for details). Smoothing is the country-level coefficient from an OLS regression of loan loss provisions on earnings before provisions and tax (Ebllp). LLP Opacity is the incremental adjusted R2 attributed to Ebllp in the country-level smoothing regression. CapIndex, Private, Official, Judical and GDP are country-level control variables (see Appendix A). ROE is bank level return on equity and Size is

the natural logarithm of the bank’s assets. , , ROE and Size are all trimmed at the 1 and 99 percentiles. For

brevity main effects are included in the regression but not reported but are available upon requests. Standard errors (reported) are clustered at the bank level. Both bank type and year fixed effects are included. Data range 1995-2006. Panel A. Descriptive Statistics

Variable Mean Median StdDev

-0.0003 -0.0000 0.0258 -0.0047 -0.0012 0.1421

SIZE 7.9755 7.7313 1.8162 ROE 0.1204 0.1273 0.1729 Panel B. OLS Regressions – Risk-Shifting

Dependent Variable: Variables Predictions I II III

*Smoothing + 0.2458*** (0.009)

*LLP Opacity + 0.3533*** (0.082)

*Official 0.0234** 0.0223** (0.019) (0.010)

*CapIndex 0.0074 0.0089 (0.019) (0.019)

*Private 0.0038 -0.0043 (0.021) (0.025)

*Judicial -0.0161*** -0.0150*** (0.004) (0.004)

*Size -0.0194*** -0.0201*** (0.007) (0.007)

*ROE 0.0018 0.0053 (0.022) (0.022)

*GDP 0.0012 0.0004 (0.003) (0.003)

0.0931*** -0.0087 0.0268 (0.034) (0.211) (0.209)

R2 0.3375 0.6893 0.6836 Observations 3,949 3,061 3,061 ***, **, * indicates significance at the 0.01, 0.05 and 0.10 level respectively.

IPP V

IPP V

IPP V

IPPV

IPP

V

V

V

V

V

V

V

V

V

V

39

Table 6 Smoothing, LLP Opacity and Risk-Shifting: Controlling for Poor Performance

OLS regression results of changes in IPP ( ) on changes in asset risk ( ) interacted with country-level

institutional features. Following Merton (1977) is the fair value of the deposit insurance premium and is

the change in the underlying assets of the firm (see Appendix B for details). Smoothing is the country-level coefficient from an OLS regression of loan loss provisions on earnings before provisions and tax (Ebllp). LLP Opacity is the incremental adjusted R2 attributed to Ebllp in the country-level smoothing regression. CapIndex, Private, Official, Judical and GDP are country-level control variables (see Appendix A). ROE is bank level return on equity and Size is the natural logarithm of the bank’s assets. Low(High) ROE is defined as the 1st (5th) quintile of the ROE distribution.

, and Size are all trimmed at the 1 and 99 percentiles. For brevity main effects are included in the

regression but not reported but are available upon requests. Standard errors (reported) are clustered at the bank level. Both bank type and year fixed effects are included. Data range 1995-2006. Panel A. Smoothing Dependent Variable: Variables Low ROE High ROE Low ROE High ROE

*Smoothing 0.4553*** 0.0960 (0.079) (0.099)

*Official 0.0338*** -0.0156** (0.009) (0.008)

*CapIndex -0.0410 -0.0044** (0.035) (0.018)

*Private 0.1035** -0.0585*** (0.037) (0.019)

*Judicial -0.0155** -0.0011 (0.006) (0.007)

*Size -0.0290** -0.0151 (0.014) (0.010)

*GDP 0.0061* -0.0184*** (0.004) (0.005)

0.1646*** 0.0572 -0.0850 0.8006*** (0.037) (0.036) (0.204) (0.259)

R2 0.7806 0.1694 0.9330 0.2356 Observations 578 591 578 591 ***, **, * indicates significance at the 0.01, 0.05 and 0.10 level respectively.

IPP V

IPP V

IPP V

IPP

V

V

V

V

V

V

V

V

40

Panel B. LLP Opacity Dependent Variable: Variables Low ROE High ROE

*LLP Opacity 0.8011*** 0.2557 (0.088) (0.245)

*Official 0.0411*** -0.0159* (0.011) (0.009)

*CapIndex -0.0575** -0.0454 (0.023) (0.032)

*Private 0.1306*** -0.0626*** (0.030) (0.023)

*Judicial -0.0110** 0.0012 (0.005) (0.006)

*Size -0.0282*** -0.0186 (0.008) (0.016)

*GDP 0.0056* -0.0186 (0.003) (0.016)

-0.1762 0.8225** (0.220) (0.400)

R2 0.9348 0.2361 Observations 578 591

IPP

V

V

V

V

V

V

V

V

41

Table 7 Smoothing, LLP Opacity and Risk-Shifting: Additional Controls

OLS regression results of changes in IPP ( ) on changes in asset risk ( ) interacted with country-level

institutional features. Following Merton (1977) is the fair value of the deposit insurance premium and is

the change in the underlying assets of the firm (see Appendix B for details). Smoothing is the country-level coefficient from an OLS regression of loan loss provisions on earnings before provisions and tax (Ebllp). LLP Opacity is the incremental adjusted R2 attributed to Ebllp in the country-level smoothing regression. CapIndex, Private, Official, Judical and GDP are country-level control variables (see Appendix A). ROE is bank level return on equity and Size is

the natural logarithm of the bank’s assets. , , ROE and Size are all trimmed at the 1 and 99 percentiles. For

brevity main effects are included in the regression but not reported but are available upon requests. Standard errors (reported) are clustered at the bank level. Both bank type and year fixed effects are included. Data range 1995-2006. Panel A. Smoothing Variable Dependent Variable:

*Smoothing 0.2328** 0.2720** 0.2667** 0.2553** 0.2464** (0.108) (0.109) (0.099) (0.121) (0.101)

*Disclosure -0.0349 0.0495 0.0218 0.0091 -0.0406 (0.133) (0.147) (0.148) (0.158) (0.122)

*StateBank 0.1200* 0.1174* (0.067) (0.061)

*Rights -0.1087 -0.0860 (0.072) (0.064)

*Liquidity -0.0002 0.0002 (0.001) (0.001)

*MrktCap -0.0001 -0.0001 (0.001) (0.002)

*Official 0.0147 0.0237** 0.0254** 0.0228** 0.0101 (0.011) (0.011) (0.011) (0.011) (0.008)

*CapIndex -0.0060 0.0082 0.0094 0.0099 -0.0076 (0.021) (0.021) (0.020) (0.023) (0.020)

*Private 0.0146 -0.0007 0.0050 0.0129 0.0131 (0.016) (0.022) (0.017) (0.025) (0.023)

*Judicial -0.0063 -0.0109 -0.0149 -0.0145 -0.0033 (0.011) (0.010) (0.010) (0.009) (0.010)

*Size -0.0191*** -0.0199*** -0.0195*** -0.0197*** -0.0194*** (0.007) (0.007) (0.007) (0.007) (0.007)

*ROE -0.0012 0.0039 0.0004 0.0033 0.0043 (0.021) (0.020) (0.021) (0.021) (0.019)

*GDP 0.0017 0.0012 0.0010 0.0015 0.0022 (0.003) (0.003) (0.003) (0.003) (0.003)

0.0745 -0.0103 -0.0606 -0.0467 0.1704 (0.339) (0.343) (0.308) (0.381) (0.289)

R2 0.6956 0.6928 0.6908 0.6919 0.7011 Observations 3,054 3,054 3,054 3,054 3,054 ***, **, * indicates significance at the 0.01, 0.05 and 0.10 level respectively.

IPP V

IPP V

IPP V

IPP

V

V

V

V

V

V

V

V

V

V

V

V

V

V

42

Panel B. LLP Opacity Variable Dependent Variable:

*LLP Opacity 0.3761** 0.4689*** 0.3100** 0.3342** 0.4834*** (0.161) (0.165) (0.131) (0.179) (0.160)

*Disclosure -0.0232 0.1048 -0.0406 -0.0232 0.0058 (0.130) (0.148) (0.121) (0.144) (0.113)

*StateBank 0.1660** 0.1721*** (0.071) (0.066)

*Rights -0.1724** -0.2015*** (0.075) (0.068)

*Liquidity 0.0000 0.0005 (0.001) (0.001)

*MrktCap -0.0001 -0.0001 (0.001) (0.002)

*Official 0.0120 0.0244** 0.0200** 0.0204* 0.0049 (0.011) (0.011) (0.008) (0.012) (0.006)

*CapIndex -0.0088 0.0011 0.0076 0.0097 -0.0141 (0.020) (0.021) (0.021) (0.024) (0.017)

*Private 0.0145 -0.0093 -0.0064 0.0001 0.0084 (0.017) (0.024) (0.022) (0.027) (0.021)

*Judicial -0.0029 -0.0082 -0.0132 -0.0127 0.0017 (0.009) (0.009) (0.009) (0.008) (0.009)

*Size -0.0195*** -0.0209*** -0.0201*** -0.0203*** -0.0200*** (0.007) (0.007) (0.007) (0.007) (0.007)

*ROE -0.0022 0.0106 0.0037 0.0052 0.0150 (0.021) (0.022) (0.021) (0.021) (0.019)

*GDP 0.0012 0.0003 0.0004 0.0007 0.0020 (0.003) (0.003) (0.004) (0.003) (0.003)

0.0939 -0.0198 0.0871 -0.0434 0.2584 (0.306) (0.315) (0.220) (0.361) (0.199)

R2 0.6950 0.6903 0.6853 0.6863 0.7064 Observations 3,054 3,054 3,054 3,054 3,054 ***, **, * indicates significance at the 0.01, 0.05 and 0.10 level respectively.

IPP

V

V

V

V

V

V

V

V

V

V

V

V

V

V

43

Table 8

Smoothing and Risk-Shifting: Controlling for Differences in Market Efficiency OLS regression results of changes in IPP ( ) on changes in asset risk ( ) interacted with country-level

institutional features. Following Merton (1977) is the fair value of the deposit insurance premium and is

the change in the underlying assets of the firm (see Appendix B for details). Smoothing is the country-level coefficient from an OLS regression of loan loss provisions on earnings before provisions and tax (Ebllp). EfficientMrkt is an indicator coded 1 (0) for markets that are classified as developed or efficient (Griffin et al., 2007). CapIndex, Private, Official, Judical and GDP are country-level control variables (see Appendix A). ROE is bank level return on equity and

Size is the natural logarithm of the bank’s assets. , , ROE and Size are all trimmed at the 1 and 99

percentiles. For brevity main effects are included in the regression but not reported but are available upon requests. Standard errors (reported) are clustered at the bank level. Both bank type and year fixed effects are included. Data range 1995-2006.

Variables Dependent Variable:

*Smoothing 0.2815*** (0.051)

*EfficientMrkt -0.0791 (0.083)

*Official 0.0206** (0.009)

*CapIndex 0.0116 (0.016)

*Private -0.0016 (0.022)

*Judicial -0.0300** (0.012)

*Size -0.0206*** (0.007)

*ROE 0.0051 (0.023)

*GDP 0.0014 (0.002)

R2 0.6924 Observations 3,061

IPP V

IPP V

IPP V

IPP

V

V

V

V

V

V

V

V

V

44

References:

Ahmed, A., C. Takeda, and S. Thomas. 1999. “Bank loan loss provisions: a reexamination of capital management, earnings management and signaling effects.” Journal of Accounting and Economics 28: 1-25.

Allen, F., and E. Carletti. 2008. “Mark-to-market accounting and liquidity pricing.”

forthcoming in the Journal of Accounting and Economics. Volume 45, Issues 2-3, August: 358-378.

Arya, A., J. Glover, and S. Sunder. 2003. “Are unmanaged earnings always better for

shareholders?” Accounting Horizons 17: 111. Basel Committee on Banking Supervision, 1991. Proposals for the inclusion of general

provisions and general loan-loss reserves in capital. February, Bank for International Settlements.

Basel Committee on Banking Supervision (BCBS). 2001. “The New Basel Capital

Accord.” Basel Committee on Banking Supervision, Second Consultative Paper. January. Basel, Switzerland.

Barth, J., G. Caprio, and R. Levine. 2004. “Bank supervision and regulation: What works

best?” Journal of Financial Intermediation 13: 205-248. Barth, J., G. Caprio, and R. Levine. 2006. Rethinking Bank Supervision and Regulation:

Till Angels Govern, Cambridge, UK: Cambridge University Press. Barth, J., G. Caprio, and R. Levine. 2007. “Bank Regulations are Changing: But for

Better or Worse?” Working Paper. World Bank. Beatty, A., S. Chamberlain, and J. Magliolo. 1995. “Managing financial reports of

commercial banks: The influence of taxes, regulatory capital, and earnings.” Journal of Accounting Research 33 (Autumn): 231-261.

Beatty, A. and S. Liao. 2009. “Regulatory capital ratios, loan loss provisioning and pro-

cyclicality” Working Paper The Ohio State. Beaver, William H., and Ellen E. Engel. 1996. “Discretionary Behavior with Respect to

Allowances for Loan Losses and the Behavior of Security Prices.” Journal of Accounting and Economics 22 (June): 177–206.

Beaver, W., Eger, C., Ryan, S., Wolfson, M., 1989. Financial reporting, supplemental

disclosures, and bank share prices. Journal of Accounting Research 27, 157–178

45

Beck, T., A. Demirgüç-Kunt, and R. Levine. 2006. “Bank Supervision and Corruption in Lending,” Journal of Monetary Economics 53(8), 2131-2163.

Benston, G. and L. Wall. 2005. “How should banks accounting for loan losses?”

Economic Review: 19-38. Bliss, R. and M. Flannery. 2002. “Market discipline in the governance of US bank

holding companies: monitoring vs. influencing” European Finance Review 6: 361-396.

Blum, J. 1999. “Do capital adequacy requirements reduce risks in banking.” Journal of

Banking and Finance 23: 755-771. Borio, C., C. Furfine, and P. Lowe. 2000. “Procycliclity of the financial system and

financial stability issues and policy options” BIS Paper Series. Chaney, P. and C. Lewis. 1995. “Earnings management and firm valuation under

asymmetric information” Journal of Corporate Finance 1: 319-345. Collins, J., D. Shackelford, and J. Whalen. 1995. “Bank differences in the coordination of

regulatory capital, earnings, and taxes.” Journal of Accounting Research (Autumn) 33: 263-291.

Cordella, T., and E. Yayati. 2003. “Bank Bailouts: Moral Hazard vs. Value Effect.”

Journal of Financial Intermediation 12: 300-330. Demirgüç-Kunt, A., E. Detragiache, and T. Tressel. 2006. “Banking on the Principles:

Compliance with Basel Core Principles and Bank Soundness,” Working Paper. World Bank.

Demirgüç-Kunt, A., B. Karacaovali, and L. Laeven. 2005. “Deposit Insurance Around

the World: A Comprehensive Database.” Working Paper. World Bank. Demski, J. 1998. “Performance measure manipulation” Contemporary Accounting

Research 15: 261-286. Duan, J., A. Moreau, and S. Sealey. 1992. “Fixed-rate Deposit Insurance and Risk-

shifting Behavior at Commercial Banks.” Journal of Banking and Finance 16: 715-742.

Dugan, J. 2009. “Loan Loss Provisioning and Pro-cyclicality.” Remarks by John C.

Dugan, Comptroller of the Currency, before the Institute of International Bankers, March 2, 2009.

46

Eisdorfer, A., 2008. “Empirical evidence of risk shifting in financially distressed firms” Journal of Finance 63: 609-637.

Fernández de Lis, S and J Martinez Pagés and J Saurina. 2001. “Credit Growth, Problem

Loans and Credit Risk Provisioning in Spain.” in Bank of International Settlement Papers, No 1, Basel, March.

Financial Accounting Standards Board (FASB). 2009. “Accounting for financial

instruments: summary of decisions reached to date as of October 26, 2009.” Norwalk CT. .

Financial Stability Forum, 2009. “Report of the financial stability forum on addressing

procyclicality in the financial system.” April 2, 2009. Flannery, M., and A. Thakor. 2006. “Accounting, Transparency and Bank Stability.”

Journal of Financial Intermediation 15: 281-284. Flannery, M., “Using Market Information in Prudential Bank Supervision: A Review of

the U.S. Empirical Evidence,” Journal of Money, Credit and Banking, 30 (3), 1998, pp. 273–305.

Fonseca, Ana Rosa, and Francisco Gonzalez. 2008.” Cross-country determinants of bank

income smoothing by managing loan-loss provisions.” Journal of Banking & Finance 32: 217–228.

Foos, D., L. Norden, and M. Weber. 2009. “Loan Growth and Riskiness of Banks”

Working Paper, University of Mannheim. Francis, J., R. Lafond, P. Olsson, and K. Schipper. 2004. “Costs of Equity and Earnings

Attributes” Accounting Review 79: 967-1010. Greenwald, M.B., Sinkey Jr., J.F.. 1988. Bank loan-loss provisions and the income-

smoothing hypothesis: An empirical analysis, 1976–1984. Journal of Financial Services Research 1, 301–318.

Griffin, J., P. Kelly and F. Nardari. 2007. “Measuring short-term international stock

market efficiency” Working Paper University of Texas-Austin. Hovikimian, A., and E. Kane. 2000. “Effectiveness of Capital Regulation at U.S.

Commercial Banks, 1985 to 1994,” Journal of Finance 55: 451-469. Hovikimian, A., E. Kane, and L. Laeven. 2003. “How Country and Safety-Net

Characteristics Affect Bank Risk-Shifting.” Journal of Financial Services Research 23: 177-204.

47

Huizinga H. and L. Laeven. 2009. “Accounting discretion of banks during a financial crisis” Working Paper IMF.

International Accounting Standards Board, (IASB) 2009. Request for information, June

2009 IASB. Kanagaretnam, K., G.Krishnan, and G. Lobo. 2009. “Is the market valuation of banks’

loan loss provision conditional on auditor reputation?” Journal of Banking & Finance 33: 1039–1047.

Kane, E. 2004. “Financial Regulation and Bank Safety Nets: An International

Comparison.” Working Paper. Boston College. La Porta, R., F. Lopez-de-Silanes, A. Shleifer. 2006. “What works in securities laws?”

Journal of Finance 61: 1-32. La Porta, R., F. Lopez-de-Silanes, A. Shleifer. 2002. “Government ownership of banks.”

Journal of Finance 57: 265-301. La Porta, R., F. Lopez-de-Silanes, A. Shleifer, and R. Vishny. 1998. “Law and Finance.”

Journal of Political Economy 106: 1113-1155. Laeven, L. and R. Levine. 2009. Bank governance, regulation and risk taking. Journal of

Financial Economics 93 (2): 259-275. Laeven, L. and G. Majnoni. 2003. “Loan loss provisioning and economic slowdowns:

Too much, Too late?” Journal of Financial Intermediation 12: 178-197. Lang, M., J. Raedy, and J. Yetman. 2003. “How representative are firms that are cross

listed in the United States? An analysis of accounting quality.” Journal of Accounting Research 41: 363-386.

Leuz, C., D. Nanda, and P. Wysocki. 2003. “Earnings management and institutional

factors: An international comparison.” Journal of Financial Economics 69: 505-527. Liu, C., and S. Ryan. 2006. “Income Smoothing over the Business Cycle: Changes in

Banks’ Coordinated Management of Provisions for Loan Losses and Loan Charge-Offs form the Pre-1990 Bust to the 1990s Boom” The Accounting Review 81: 421-441.

Liu, C., Ryan, S., 1995. The effect of bank loan portfolio composition on the market

reaction to and anticipation of loan loss provisions. Journal of Accounting Research 33, 77–94.

48

Liu, C., Ryan, S., Wahlen, J., 1997. Differential valuation implications of loan loss provisions across banks and fiscal quarters. Accounting Review 72, 133–146.

Loktionov, Y. 2009. “Does accounting quality mitigate risk shifting?” Working Paper

USC. Merton, R. 1977. “An Analytic Derivation of the Cost of Deposit Insurance and Loan

Guarantees,” Journal of Banking and Finance 1: 3-11. Moyer, S. 1990. “Capital adequacy ratio regulations and accounting choices in

commercial banks.” Journal of Accounting and Economics 13 (July): 123-154. Nier, E., and U. Baumann. 2006. “Market discipline, disclosure and moral hazard in

banking,” Journal of Financial Intermediation 15: 332-361. Plantin, G., H. Sapra, and H. Shin. 2007. “Marking to Market: Panacea or Pandora’s

Box?” forthcoming in the Journal of Accounting Research. Rochet, J.C. 2005. “Prudential Policy.” Monetary and Economic Studies (Special

Edition) October: 93-119. Rochet, J.C. 1992. “ Capital requirements and the behavior or commercial banks.”

European Economic Review 36: 1137-1170. Ronn, E., and A. Verma. 1986. “Pricing Risk-adjusted Deposit Insurance: An Option-

Based Model.” Journal of Finance 41: 871-895. Sankar, R. and K.R. Subramanyam. 2001. “Reporting discretion and private information

communication through earnings.” Journal of Accounting Research 39: 365-386. Tadesse, S. 2006. “The economic value of regulated disclosure: Evidence from the

banking sector.” Journal of Accounting and Public Policy 25: 32-70. Trueman, B. and S. Titman. 1988. “An explanation for accounting income smoothing”

Journal of Accounting Research 26: 127-139 Tucker, J. and P. Zarowin. 2006. “Does income smoothing improve earnings

informativeness?” Accounting Review 81: 251-270. US Treasury. 2009. “A new foundation: rebuilding financial supervision and regulation”

Financial Regulatory Reform. Vyas, D. 2009. “Financial reporting transparency of US financial institutions during the

current economic crisis” Working Paper University of Toronto.

49

Wall, L. and T. Koch. 2000. “Bank loan-loss accounting: a review of theoretical and empirical evidence” Economic Review: 1-19.

Watts, R. and J. Zimmerman. 1986. Positive accounting theory. Prentice-Hall. Whalen, J. 1994. “The nature of information in commercial bank loan loss disclosures.”

The Accounting Review 69 (July): 455-478.