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Corporate Governance of Banks and Financial Stability:

International Evidence1

Deniz Anginer

Virginia Tech, Pamplin College of Business

Asli Demirguc-Kunt

Word Bank

Harry Huizinga

Tilburg University and CEPR

Kebin Ma

Warwick Business School

This draft: December 2015

Abstract: This paper finds that shareholder-friendly corporate governance is positively

associated with bank insolvency risk and a bank’s contribution to financial-sector

systemic risk for an international sample of banks over the 2004-2008 period. Banks are

special in that ‘good’ corporate governance increases bank risk relatively more for banks

that are large and located in countries with generous financial safety nets, as banks aim to

exploit the financial safety net compared to non-financial firms. ‘Good’ corporate

governance is specifically associated with higher asset volatility, more non-performing

loans, and a lower tangible capital ratio. Furthermore, ‘good’ corporate governance is

associated with more bank risk taking at times of rapid economic expansion. These

results underline the importance of the financial safety net and too-big-to-fail policies in

encouraging excessive risk-taking by banks.

Key words: Corporate governance; Bank insolvency; Systemic risk

JEL Classification: G21, M21

1 Anginer: Danginer@gmail.com; Demirguc-Kunt: Ademirguckunt@worldbank.org; Huizinga:

Huizinga@uvt.nl; Ma: Kebin.ma@gmail.com. We thank an anonymous referee and participants at the 18th

annual International Banking Conference at the Federal Reserve Bank of Chicago for useful comments and

suggestions. This paper’s findings, interpretations, and conclusions are entirely those of the authors and do

not necessarily represent the views of the World Bank, its Executive Directors, or the countries they

represent.

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1. Introduction

Corporate managers may be more risk averse than shareholders, as corporate

bankruptcy generally causes managers to lose their jobs, part of their personal wealth and

their reputation. ‘Good’ corporate governance - promoting the interests of shareholders –

may serve to counteract managers’ bias against risk taking. Consistent with this notion,

John, Litov, and Yeung (2008) find that ‘better’ corporate governance in the form of

stronger investor protection brings about increased risk-taking and higher growth for an

international sample of non-financial firms.

For financial institutions, the calculus regarding the optimal degree of risk taking

is different compared to non-financial firms, as banks tend to be supported by the

financial safety net if they become distressed. Banks, in particular, benefit from deposit

insurance and may receive generous public support to prevent their failures. The financial

safety net provides banks with an incentive to take on excessive risks in order to increase

the value of these benefits. Hence, the association between risk taking and corporate

governance may be different in the case of banks (see for example, Laeven, 2013).

Large banks may benefit relatively more from the financial safety net, as they

may be deemed too big to fail by regulators (see Acharya, Anginer and Warburton, 2014,

and Bertay, Demirguc-Kunt, and Huizinga, 2013). For this reason, shareholder-friendly

corporate governance may increase risk taking more in the case of large banks. Similarly,

banks may gain more from increasing risk if the financial safety net is more generous.

Therefore, shareholder-friendly corporate governance is likely to increase bank risk

taking especially in countries with generous financial safety nets.

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This paper empirically examines the relationships between bank risk and

corporate governance for an international sample of banks from 22 countries over the

2004-2008 period. We distinguish between a bank’s stand-alone insolvency risk, and a

bank’s contribution to systemic risk to gauge the threat a bank poses to overall financial

stability. Specifically, an individual bank’s insolvency risk is proxied by the Z-score and

the distance to default, while a bank’s contribution to financial-sector systemic risk is

captured by the marginal expected shortfall (MES) variable proposed by Acharya, Engle

and Richardson (2012), and alternatively by the CoVaR proposed by Adrian and

Brunnermeier (2015). Following Aggarwal et al. (2009), we use an overall index of

shareholder-friendly corporate governance dealing with board composition,

compensation, auditing and takeover-related issues based on data from Institutional

Shareholder Services.

We find that a bank’s insolvency risk and its contribution to systemic risk are both

positively associated with the overall index of shareholder-friendly corporate governance.

This positive relationship between bank risk and shareholder-friendly corporate

governance is robust to instrumental variables estimation, where a bank’s corporate

governance is instrumented by the annual country-mean value of the corporate

governance variable for all non-financial firms.

Furthermore, we find that bank insolvency and systemic risks are positively

associated with shareholder-friendly corporate governance especially for large banks and

for banks located in countries with generous financial safety nets. These results are

consistent with the view that shareholder-friendly corporate governance increases bank

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risk more if the additional bank risk increases a bank’s contingent claim on the financial

safety net.

Going beyond measures of insolvency and systemic risk, we also examine the

‘channels’ through which a “better governed” bank takes on more risk. On the asset side,

we find that asset volatility derived from Merton’s option pricing model, and the share of

non-performing loans in total loans, are positively related to ‘good’ corporate

governance. On the liability side, we find a negative relationship between a bank’s

tangible equity ratio and the corporate governance index.

Our results further suggest that corporate governance affects the relationship

between bank risk taking and the business cycle. Specifically, we find that banks with

‘good’ corporate governance report less non-performing loans at times of high economic

growth. This suggests that banks with ‘good’ corporate governance bias their reporting of

non-performing loans downward during periods of rapid economic expansion so as to

preserve capital to be able to continue to increase credit. In addition, we see that banks

with ‘good’ corporate governance have relatively low tangible capital ratios when the

economy grows rapidly.

Non-financial firms are less likely to benefit from the financial safety net

compared to banks. This suggests that the relationship between shareholder-friendly

corporate governance and firm insolvency risk should be weaker for non-banks than for

banks. We expand our sample of international banks to include non-bank corporations,

and find that the positive relationship between insolvency risk and shareholder-friendly

corporate governance is significantly more pronounced for banks than for non-banks,

especially when we compare large banks to large non-banks.

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Finally, to further alleviate endogeneity concerns, we examine the impact of new

governance rules mandating greater board independence, that were adopted in 2003 by

stock exchanges in the US, on bank insolvency risk. The new rules increased board

independence for some banks but not others, as only banks that were initially non-

compliant with the new rules had to increase their board independence. We find that

insolvency risk increased relatively more at banks that were directly affected by the

reforms. This is strong evidence that shareholder-friendly corporate governance causes

higher bank insolvency risk.

Our study fits in an emerging literature that has addressed the impact of corporate

governance on bank risk taking.2 Pathan (2009) finds that small boards and boards that

are not controlled by the CEO lead to additional bank risk as reflected in market

measures of risk and the Z-score for a sample of US bank holding companies over the

1997-2004 period. Chen, Steiner, and Whyte (2006), find a positive impact of option-

based executive compensation and wealth on market measures of risk for a sample of US

commercial banks during the period 1992-2000. DeYoung, Peng, and Yan (2013) find

that CEO risk-taking incentives lead to riskier business policy decisions (with respect to

loans to businesses, non-interest based banking activities, and investment in mortgage-

backed securities) at US commercial banks over the 1994-2006 period, especially for

larger banks and in the second half of the sample period after deregulation in the banking

sector. Calomiris and Carlson (2014) examine bank ownership and risk-taking at US

2 Recent surveys are offered by Becht, Bolton, and Roell (2011) and Mehran, Morrison and Shapiro (2012).

Stulz (2015) discusses how corporate governance and risk management should be designed to ensure that

banks only take good risks that add value.

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banks in the 1890s, and find that higher managerial ownership is associated with lower

bank default risk.

Several papers have also examined how banks with different corporate

governance regimes fared during the crisis, with mixed results. Berger, Imbierowicz, and

Rauch (2015) find that high shareholdings of lower-level management imply a

substantially higher probability of bank failure for US commercial banks over the 2007-

2010 period. Fahlenbrach and Stulz (2011) find some evidence that US banks with CEOs

whose incentives were better aligned with the interests of shareholders in 2006 had worse

share price performance during the subsequent crisis. Ellul and Yerramilli (2013) report

that US bank holding companies that had a strong and independent risk management

function in place before the onset of the financial crisis fared better in terms of operating

and stock performance during the crisis.

However, multi-country studies of bank corporate governance and risk taking are

relatively scarce. Laeven and Levine (2009) examine the relationship between bank

ownership and bank risk taking for an international sample of banks. They find that

stronger cash flow rights of large owners are associated with greater bank risk, consistent

with the hypothesis that bank shareholders favor risk-taking as compared to managers

and creditors. These authors also consider the interaction between bank regulation and

ownership, finding that deposit insurance is associated with an increase in risk only when

the bank has a large equity holder. More recently, using international data, Erkens,

Hung, and Matos (2012) find that financial institutions with more independent boards and

higher institutional ownership experienced worse stock returns during the global financial

crisis.

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Our contribution to this literature is three-fold. First, we use international bank-

level data from 22 countries to study the association between bank individual and

systemic risk measures and corporate governance, adding to a literature that has mostly

relied on US data. Using multi-country data enables us to exploit differences across

country safety nets to study how the relationship between bank risk-taking and corporate

governance varies with the generosity and credibility of the safety net and banks’ ability

to engage in risk-shifting. Second, this paper is the first to study the relationship between

a bank’s corporate governance and its contribution to systemic risk. Third, we are able to

study how banks increase their risk-taking with more shareholder friendly corporate

governance, identifying increased asset risk, more non-performing loans, and reduced

capitalization as potential channels.

Overall, our findings on the interaction of bank-level corporate governance

variables and the financial safety net have important implications for corporate

governance reforms in the banking sector, as policy makers question the extent to which

governance failures have contributed to excessive risk taking and financial instability. In

particular, our results suggest that one has to be cautious to call for ‘better’ corporate

governance at banks as long as generous financial safety nets and too-big-to-fail policies

are in place, as this may actually induce banks to take on more risk with potentially

negative repercussions for the stability of the financial system.

In the remainder, section 2 discusses the data. We present the empirical results in

section 3. We start with an analysis of the relationships between corporate governance

and bank insolvency and systemic risks. Then we consider the ‘channels’ on the assets

and liabilities sides of the bank’s balance sheet through which corporate governance

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affects overall bank risk, and the relationship between corporate governance and bank

risk taking over the business cycle. Next, we consider the relationship between corporate

governance and insolvency risk for a sample of firms including both banks and non-

banks. Finally, we examine the impact of reform towards greater board independence in

the US on bank insolvency risk. Section 4 concludes with policy implications.

2. The data

In this study, we relate measures of bank insolvency and systemic risk to

summary indicators of corporate governance for an international sample of banks over

the 2004-2008 period. In addition, we consider the relationship between corporate

governance and insolvency risk for an international sample of firms comprising banks as

well as non-bank corporations. We describe the samples of banks only, and of both banks

and non-banks in turn.

2.1 The sample of banks

Accounting and market data necessary to construct our bank risk measures are

taken from Bankscope of Bureau Van Dijk, CRSP and Compustat Global. Data on bank

corporate governance are from the Corporate Governance Quotient database assembled

by Institutional Shareholder Services (ISS).

We examine two measures of individual bank insolvency risk. First, the Z-score

represents the number of standard deviations that a bank’s rate of return on assets has to

fall for the bank to become insolvent. The Z-score is constructed as the sum of the rate of

return on assets and the equity to assets ratio divided by the standard deviation of the

return on assets (see Table A1 in the Appendix for variable definitions and data sources).

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A higher Z-score signals that a bank has lower insolvency risk. We calculate a Z-score

for a bank, if at least three annual observations of its rate of return on assets are available.

Our second insolvency risk variable, the distance to default, measures the difference

between the asset value of the bank and the face value of its debt, scaled by the standard

deviation of the bank’s asset value (see Campbell, Hilscher and Szilagyi, 2008, p. 2899).

The distance to default variable is computed as an annual average of monthly values (see

the Appendix for details on how the distance to default is estimated).

Following the recent literature, we use two variables to measure a bank’s

contribution to systemic risk. First, following Acharya, Engle and Richardson (2012),

marginal expected shortfall (MES) is the average bank stock return when the stock

market return as a whole is in the lower tail of its distribution. Specifically, MES is

constructed as the average bank stock return when the market return is in its lowest 5%

bracket in a given year. Second, following Adrian and Brunnermeier (2015), CoVaR is

defined as the value at risk of the overall financial system conditional on a bank being in

distress and the value of risk of the overall financial system conditional on a bank being

in a normal state, where a bank’ distress and normal states are defined as a bank’s stock

return being at the 5th and 50th percentile in a given year respectively. Lower values for

MES and CoVaR signal higher bank contributions to systemic risk.3

Next, we construct several variables to capture different aspects of a bank’s

overall risk strategy. These variables reflect a bank’s asset allocation and income mix

strategies, its capitalization and funding strategies, and its overall asset growth strategy.

3 See Appendix A1 for details on how MES and CoVaR are constructed.

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To start, asset volatility is the annualized standard deviation of the asset return

computed from the Merton’s option pricing model. The asset volatility variable has a

mean of 0.05. Asset risk weight is an indicator of the average riskiness of a bank’s assets,

and is computed as the ratio of risk-weighted assets to total assets, using the risk weights

as defined in the Basle capital adequacy framework. Lower values of asset risk weight

indicate less risky assets. The asset risk weight variable has a mean of 0.70.

Bank loans are generally riskier than other investments, such as holdings of

government securities. We use the loans variable, computed as the ratio of loans to total

assets, as a proxy for asset risk. The loans variable has a mean of 0.70.

The non-performing loans variable, computed as the ratio of non-performing

loans to total loans, is an index of loan quality. On average, 1.4% of loans are non-

performing.

A bank’s asset allocation affects the composition of its income which is generally

in the form of interest income, fees, commissions and trading income. The non-interest

income variable, constructed as the ratio of net interest income to total operating income,

is an index of the riskiness of a bank’s income. It has a mean of 0.29.

On the liability side of a bank’s balance sheet, we consider three alternative

capitalization ratios. First, Tier 1 capital is a regulatory capital ratio constructed as Tier 1

capital divided by risk-weighted assets. The Tier 1 capital ratio has a mean of 11.1%.

Second, regulatory capital is a broader regulatory capital ratio computed as the sum of

Tier 1 capital and Tier 2 capital divided by risk-weighted assets with a mean of 13.0%. A

bank’s common equity can be divided into tangible common equity and non-tangible

common equity. The latter category includes tax deferred assets and mortgage servicing

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rights, which are capital categories with only limited loss absorption capacity. As a third

capital ratio, we construct the tangible capital ratio as the ratio of tangible equity divided

by tangible assets (i.e., total assets minus non-tangible assets). The tangible equity ratio

has a mean of 7.3%.

A bank’s short-term funding comprises customer and other deposits and non-

deposits such as short-term borrowing in the interbank market. The non-deposit funding

variable, computed as the share of non-deposit, short-term funding in total short-term

funding, is an index of the riskiness of a bank’s short-term funding. It has a mean of

16.8%.

High bank asset growth may signal higher bank risk, as a bank may only be able

to grow fast by investing in riskier assets, for instance by lending to customers that

represent higher risk. Our asset growth variable is the growth rate of total assets, with a

mean value of 6.0%.

In addition, banks with highly procyclical asset growth rates may be more risky,

since such banks may be overly optimistic about asset quality at the peak of the business

cycle. We construct the asset procyclicality variable as the correlation between a bank’s

asset growth rate and the GDP growth rate. The mean asset procyclicality variable is

0.13. Similarly, the lending procyclicality variable is the correlation between a bank’s

loan growth rate and the GDP growth rate with a mean of 0.20. In addition, we consider

the correlations of a bank’s non-performing loan rate and its tangible capital ratio with

the GDP growth rate with means of -0.38 and 0.18, respectively.

Our corporate governance variables are indices that summarize extensive

information on detailed governance attributes that are indicative of increased power of

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minority shareholders. We use the indices as formulated by Aggarwal et al. (2009) based

on individual governance attributes assembled by Institutional Shareholder Services. The

individual attributes are dummy variables that take on a value of 1 if the characteristic is

relatively shareholder-friendly, and a value of zero otherwise. An overall index, called

corporate governance, summarizes information on 44 attributes, and it is scaled to range

between 0 and 1. In addition, there are four sub-indices, labeled board, compensation and

ownership, auditing and takeover that summarize information on 25, 10, 3 and 6

attributes related to these various aspects of corporate governance, respectively. The

takeover sub-index, for instance, has a higher score, if there are fewer corporate

governance-related barriers to takeovers. A listing of the individual attributes that are

represented by the overall index, and the four sub-indices, is provided in Table A2 in the

Appendix. This detailed information on corporate governance is available for banks

located in 22 countries. For the country coverage, see Table A3 in the Appendix.

Overall corporate governance has become more shareholder-friendly over the

2003-2007 period. As seen in Figure 1, the average overall index increased from 0.58 in

2003 to 0.63 in 2007 for US banks, while it increased from 0.52 to 0.59 for non-US

banks. These differential trends in corporate governance for US and non-US banks (and,

therefore, also for individual banks) allow us to estimate relationships between bank risk

variables and corporate governance in specifications that include bank fixed effects.

The financial safety net variable is a summary measure of the strength of the

financial safety net obtained through a principal components analysis of deposit

insurance design features following Demirguc-Kunt and Detragiache (2002).

Specifically, we collect data on deposit insurance characteristics in the year 2003 from

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Demirguc-Kunt, Karacaovali and Laeven (2005), and construct financial safety net as the

sum of four principal components derived from eight deposit insurance characteristics:

(1) existing coverage of foreign currency deposits, (2) existing coverage of interbank

deposits, (3) an absence of coinsurance, (4) coverage per depositor per bank per account,

(5) existence of funding ex ante, (6) existence of funding by the government, (7)

existence of a risk-insensitive insurance premium, and (8) the ratio of insurance coverage

and deposits per capita. In each instance, a higher value for the deposit insurance feature

suggests a more generous financial safety net and a greater potential to induce bank risk

taking.

In the analysis, we use several bank-level control variables. The assets variable,

constructed as the log of a bank’s total assets, proxies for the bank’s absolute size. Larger

banks may pursue riskier banking strategies, if they are considered to be too big to fail. In

addition, the assets to GDP variable, or total bank assets divided by GDP, represents the

bank’s size relative to the national economy with a mean of 0.06. The overhead variable

is constructed as overhead expenses divided by total assets. The average overhead

variable is 0.03. Inefficient banks with large overhead expenses may choose relatively

risky bank strategies to maintain a certain expected return on assets. Finally, the collateral

variable is the ratio of assets that can be easily used as collateral divided by total assets.

The collateral variable on average is 0.27. Banks with assets that can be used as collateral

may find it easier to pursue risky banking strategies, as their financial costs may be less

sensitive to overall bank risk.

Finally, we include several macroeconomic and country-level institutional control

variables. Inflation is the consumer price inflation rate. GDP growth is the rate of real

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GDP growth. GDP per capita is GDP per capita in thousands of constant U.S. dollars.

The variable restrict is a composite index of regulatory restrictions on bank activities

from Barth et al. (2004). Specifically, it is an indicator of the degree to which banks face

regulatory restrictions on their activities in securities markets, insurance, real estate, and

their ownership of shares in non-financial firms. Capital stringency is an index of

regulatory oversight of bank capital, summarizing information about the nature and the

magnitude of bank capital requirements, with higher values indicating greater stringency.

Official is an index of the power of the commercial bank supervisory agency to undertake

specific actions to prevent and correct problems at a bank, with higher values indicating

greater power. Diversification is an index of loan diversification guidelines imposed on

banks. Finally, financial freedom is an index of financial market freedoms available from

the Heritage Foundation.

2.2 The sample of banks and non-banks

Summary statistics for the sample of banks and non-banks are provided in Panel

A of Table 2. We use the same two risk measures, the Z-score and the distance to default,

for both banks and non-bank corporates. The average Z-score and the average distance to

default for the combined bank and corporate sample are 3.06 and 5.68, respectively.

However, we use a different set of controls when we compare financial firms to non-

financial firms, since some variables, such as the capital stringency variable, are only

applicable to banks. Following the literature, we use the book-to-market ratio, the return

on assets, and firm size proxied by the assets variable as control variables. Firms with

lower market valuations may be closer to insolvency, and hence display higher

insolvency risk. To reflect this, we use the Book-to-market variable, which is the book

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value of total equity divided by the market value of total equity with a mean of 3.09.

More profitable firms with a higher return on assets may have lower insolvency risk.

ROA is the return on assets with a mean of 0.66%. Finally, larger firms, especially banks,

may pursue riskier strategies, if they are deemed to big to fail. The average assets

variable is 6.71.

3. Empirical results

3.1 Bank insolvency risk and corporate governance

We begin our analysis by examining the baseline relationship between bank risk and

corporate governance. In particular, we estimate the following panel model for an

international sample of banks:

Riskijt = α + β0Governanceijt−1 + β1Xijt−1 + β2Zjt−1 + γi + δt + ϵit (1)

Riskijt is a measure of risk for bank i in country j at time t. We use four different measures

of risk. Z-score and distance to default measure bank level risk, while MES and CoVar

measure a bank’s contribution to the risk of the system. Governanceijt is a corporate

governance variable. As mentioned earlier, we use an overall governance index and its

major subcomponents following Aggarwal et al. (2009). Xijt is a set of firm-level

controls, and Zjt is a set of country-level controls as described in Section 2. Finally, we

include firm fixed effects, γi, and year fixed effects, 𝛿𝑡, to control for time-invariant firm

level heterogeneity and macro shocks that affect all firms in a given year. For all

governance measures we use, a higher value of the Governanceijt variable indicates that

corporate governance better serves the interests of shareholders. Shareholders potentially

stand to gain from higher bank risk to the extent that they can shift risk to debt holders

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and the financial safety net. Lower values of all four bank risk measures, Z-score,

distance to default, MES, and CoVaR, point towards higher risk. Accordingly, in the

regression specified in equation (1), we expect to find that β1 < 0. In the estimation, we

cluster the errors at the bank level. All independent variables are lagged by one year to

reduce endogeneity concerns.

Table 3 reports the results. In Panel A, we report regression results that include

the overall corporate governance variable, while in Panel B we report regression results

that include the four corporate governance subindices that make up the overall index. In

the Z-score regression in column 1 of Panel A, the overall corporate governance index

has a negative coefficient of -0.832 that is significant at the 10% level, suggesting that

more shareholder-friendly corporate governance increases bank insolvency risk. Among

the controls, we find that the Z-score is negatively and significantly related to the assets

and assets to GDP variables, indicating that larger absolute and relative bank size are

associated with higher bank insolvency risk. This is consistent with the notion that larger

banks take on more risk as they benefit from a too-big-to-fail status. The Z-score is

positively and significantly related to the GDP growth variable, as bank insolvency risk

may be reduced by economic growth. In addition, the Z-score is negatively and

significantly related to GDP per capita. This result may reflect that banks in wealthier

countries benefit from a more credible financial safety net, which induces them to take on

more risk. Furthermore, the Z-score is positively and significantly related to the

diversification variable, suggesting that guidelines promoting diversification contribute to

bank safety. Similarly, the Z-score is positively and significantly related to the economic

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freedom variable, as economic freedom may enable a bank to diversify into activities that

reduce overall bank insolvency risk.

In regression results reported in column 2, the dependent variable is distance to

default. Otherwise, this regression is analogous to regression results reported in column

1. We obtain similar results. The overall corporate governance index has a negative

coefficient that is significant at the 5% level, indicating that bank insolvency risk is

positively related to shareholder-friendly corporate governance.

In regressions 3 and 4, the dependent variables are MES and CoVaR which

measure a bank’s contribution to systemic risk. In both regressions, the estimated

coefficients for the corporate governance variable are negative and significant at the 1%

level, consistent with a positive relationship between shareholder-friendly corporate

governance and a bank’s contribution to systemic risk. Overall, the results of Panel A of

Table 3 suggest that bank insolvency and systemic risks vary positively with shareholder-

friendly corporate governance, consistent with our conjecture.

In Panel B, we examine the sub-components of the overall governance index

together in the same regression. We only report coefficients on the governance

subindices to save space. The results are weaker when we consider individual

components of governance. We find that the distance to default variable is negatively and

significantly related to the board-related corporate governance subindex. The MES and

CoVaR variables are negatively and significantly related to the compensation and

ownership, and takeover subindices.

As robustness checks, we used two alternative measures of bank risk and risk-

shifting: the fair value of the liability insurance implicit in the financial safety net (this is

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the IPP variable explained in Appendix A1), and average interest expense calculated as

interest expense divided by average interest-bearing liabilities. In unreported regressions

similar to those of Table 3 Panel A, these two indices of bank risk and risk-shifting are

positively and significantly related to the corporate governance variable.

Bigger banks may be riskier, because they expect to receive a more generous

treatment by bank regulators in case of insolvency because of their too-big-to-fail status.

Hence, the positive relationship between bank risk and ‘good’ corporate governance may

be driven by the larger banks in the sample. To examine whether the relationship between

bank risk and corporate governance depends on bank size, we include an interaction term

between the corporate governance variable and the assets variable in the regressions of

Panel A of Table 3. We report the results in Table 4. In regressions reported in columns

2-4, the coefficient on the variable that interacts the overall corporate governance index

with size is negative and statistically significant. This is consistent with the notion that

‘good’ corporate governance increases insolvency and systemic risks of especially large

banks, consistent with greater risk-shifting incentives for larger banks on account of their

too-big-to-fail status.

To further investigate risk-shifting by larger banks, we also examine how the

impact of corporate governance on bank risk varies with the strength of the safety net.

Countries with strong financial safety nets are more likely to bail out distressed banks

that are deemed too big to fail. Therefore, banks with shareholder-friendly corporate

governance may be riskier if they are located in country with a strong financial safety net.

To examine this, we estimate regressions that include the financial safety net variable as

an index of the strength and generosity of the financial safety net protecting banks.

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Specifically, in the regressions of Table 4 we include triple interactions of the financial

safety net, corporate governance, and assets variables (and also double interactions of

financial safety net with corporate governance and assets). We report the results in Table

5. In regressions reported in columns 1, 3 and 4, we see that the triple interaction term

involving the financial safety net variable has significant negative coefficients. This is

evidence that ‘good’ corporate governance increases insolvency and systemic risks

especially at banks that are large and located in countries with generous financial safety

nets.

3.2 Endogeneity

We recognize that corporate governance may, to some extent, be endogenously

determined. For instance, a strong preference for risk on the part of a bank’s shareholders

may jointly give rise to both considerable bank risk taking and shareholder-friendly

corporate governance. To alleviate concerns about endogeneity, we include bank fixed

effects in all regressions in the paper, thereby controlling for any time-invariant

unobservable bank characteristics that affect both bank corporate governance and bank

risk. Going beyond this, we analyze the relationship between corporate governance and

bank risk using an instrumental variables approach. In particular, we instrument for a

bank’s corporate governance variable by using the country and year average of this

variable for all non-financial firms in the country. Such country-year averages are good

instruments to consider, as a shock to a bank’s risk is unlikely to affect the corporate

governance of non-financial firms. Similar IV approaches were previously used by John,

Litov, and Yeung (2008), Aggarwal et al. (2009), and Laeven and Levine (2009). The IV

results, reported in Table 6, show negative and significant coefficients for the corporate

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governance variable in the distance to default, MES, and CoVaR regressions in columns

2-4. These IV regressions thus provide additional evidence that shareholder-friendly

corporate governance increased bank insolvency and systemic risks over the sample

period covering the years 2004-2008.

3.3 Bank risk strategies

A bank’s Z-score and its distance to default are summary measures of bank

insolvency risk that reflect a range of bank risk-related strategies associated with its asset

allocation, income mix, and capitalization and funding strategy. Next, we consider the

impact of corporate governance on a range of indicators that reflect a bank’s broader risk

strategy. To start, Table 7 reports results on the associations between a bank’s asset and

income strategies and indices of corporate governance. In regression 1, the asset volatility

variable is positively and significantly related to the overall corporate governance index

which indicates that more shareholder-friendly corporate governance is associated with

more asset risk. In regressions 2 and 3, the asset risk weight and loans variables are

positively related to the corporate governance variable, but these relationships are

statistically insignificant. Regression 4 shows that the non-performing loan rate varies

positively and significantly with the overall corporate governance variable, suggesting

that banks with shareholder-friendly corporate governance make riskier loans that more

frequently become non-performing. Finally, the non-interest income share is not

significantly related to the corporate governance variable in regression 5. Overall, the

results of Table 7 suggest that banks with shareholder-friendly corporate governance

maintain risker asset portfolios as reflected in a higher asset return volatility and a higher

non-performing loan rate.

21

Next, we consider whether corporate governance is associated with risky

capitalization, funding and growth strategies. In regressions 1-3 of Table 8, the Tier 1

capital ratio, the regulatory capital ratio, and the tangible capital ratio are negatively

related to the overall corporate governance index. In the case of the tangible capital ratio

regression 3, the negative estimated relationship between capitalization and the corporate

governance variable is statistically significant. This provides some evidence that bank

capitalization varies negatively with shareholder-friendly corporate governance.4 We do

not find that the non-deposit funding variable, as an index of relatively risky non-deposit

short-term funding, is significantly related to the corporate governance variable in

regression 4. Finally, regression 5 shows a positive and insignificant relationship between

the asset growth and corporate governance variables. Taken together, Tables 7 and 8 are

consistent with the view that banks with shareholder-friendly corporate governance

employ several strategies to increase bank risk, including higher asset return risk, higher

non-performing loan rates, and lower capitalization.

3.4 Banking procyclicality

Next, we consider how corporate governance affects the cyclicality of bank asset

growth and other proxies of bank-risk taking. Banks with shareholder-friendly corporate

governance may take on additional risk by expanding their balance sheet during

economic booms. To test this, we relate the asset procyclicality variable, which is the

correlation between bank asset growth and GDP growth, to the overall corporate

governance index in regression 1 of Table 9. This yields an estimated coefficient that is

4 Anginer, Demirguc-Kunt, Huizinga, and Ma (2013) consider in detail how board-related and takeover-

related corporate governance features and executive compensation affect capitalization strategies for an

international sample of banks over the 2003-2011 period.

22

positive and insignificant. In regression 2, we relate a similar loan procyclicality variable,

constructed as the correlation between bank loan growth and GDP, to the corporate

governance variable, yielding a positive and insignificant coefficient.

Next, we consider the correlation coefficient between the non-performing loan

rate and GDP growth. Regression 3 shows that this measure of non-performing loans

procyclicality is related negatively and significantly to the overall corporate governance

variable, indicating that banks with more shareholder-friendly corporate governance

report less non-performing loans during economic booms. This could reflect that these

banks manipulate the reporting of non-performing loans downward during periods of

high economic growth in order to preserve capital and continue to be able to expand

credit.

Finally, the tangible capital procyclicality variable is computed as the correlation

between the tangible capital ratio and GDP growth. In regression 4, the tangible capital

procyclicality variable is related negatively and significantly to the corporate governance

variable. This is evidence that banks with more shareholder-friendly corporate

governance maintain lower tangible capital ratios during economic upswings.

Overall, the results of Table 9 suggest that banks with shareholder-friendly

corporate governance tend to take more risks at the peak of the business cycle by

maintaining relatively low non-performing loans and tangible capital ratios.

3.5 Additional analyses to address endogeneity

In this section, we carry out two additional analyses to further alleviate potential

endogeneity concerns. First, we show that the effect of shareholder-friendly corporate

governance in increasing insolvency risk is significantly higher for banks compared to

23

non-financial firms. Second, we use an exogenous regulatory change in the US that

increased board independence for some banks but not others, and show that insolvency

risk increased significantly more for the banks affected by this regulatory change.

Diverging interests regarding firm risk between shareholders and management

exist at financial as well as non-financial firms. The evidence of section 3.1, however,

suggests that shareholders of banks may be especially interested in additional firm risk, as

banks in distress can potentially benefit from the financial safety net. This may imply that

insolvency risk varies more positively with shareholder-friendly corporate governance for

banks than for non-banks. Furthermore, we would expect that the shareholders of large

banks are more interested in additional risk relative to the shareholders of non-banks of

comparable size, as large banks are more likely to benefit from the financial safety net.

To test these relationships, we relate the Z-score and the distance to default to the

corporate governance variable for an international sample of firms that includes banks as

well as non-banks. To distinguish the two types of firms, we construct a dummy variable

called bank that takes on a value of one if a given firm is classified as a bank according to

ISS industry codes.5 In the analysis, we use the book-to-market, ROA, and assets

variables as controls. We allow the coefficients for these control variables to be different

for banks and non-banks by including interactions of each control variable with the bank

dummy variable. In addition, an interaction term of the corporate governance and bank

dummy variables is included to test for a differential impact of shareholder-friendly

corporate governance on insolvency risk for banks and non-bank corporations. The

results are reported in Table 10.

5 In particular, the bank dummy is set to one if the firm is in the “banks” or “diversified financials” industry

categories.

24

In the Z-score regression 1, the corporate governance variable has a positive and

significant coefficient, while the interaction of corporate governance with the bank

dummy variable has a negative and significant coefficient. These results suggest that

shareholder-friendly corporate governance increases insolvency risk at banks relatively

more, which is consistent with the view that the shareholders of banks are relatively more

interested in firm-level risk. In the distance to default regression 2, the interaction of

corporate governance with the bank dummy variable similarly has a negative and

significant coefficient. This is further evidence that insolvency risk varies more positively

with shareholder-friendly corporate governance for banks than for non-banks.6 In the Z-

score and distance to default regressions 3 and 4, we include an additional triple

interaction term of the corporate governance, bank dummy and assets variables. In both

regressions, the triple interaction term has negative and significant coefficients, consistent

with the view that the shareholders of large banks stand to gain relatively more from

increasing risk on account of their banks’ too-big-to-fail status. Overall, the results of

regressions 1-4 indicate that insolvency risk varies more positively with shareholder-

friendly corporate governance at banks than at non-banks, especially in the case of large

firms. These results are consistent with the view that shareholder-friendly corporate

governance leads a bank to adopt a higher level of risk to serve the interests of

shareholders.

6 As a robustness check, we replicated the analysis reported in columns 1-2 of Table 10 using US data on

corporate governance for banks and non-banks that are available for a longer period. In particular, as

corporate governance variables we used the G-Index introduced by Gompers, Ishii and Metric (2003)

giving rise to a sample for the period 1990-2012, and alternatively the share of independent board members

giving rise to sample for the period 2000-2012. For these samples, we obtain significant results that are

similar to those reported in Table 10 (unreported).

25

In the remainder of this section, we consider new regulations introduced in 2003

by the NYSE and NASDAQ exchanges, requiring firms to have more than 50%

independent directors, as an exogenous event affecting corporate governance.7 The new

regulations significantly increased the proportion of independent directors in some firms

but not others. The firms were required to comply with these new rules starting in 2004.8

We use the fact that some firms already had a majority of independent directors on their

boards (and thus complied with the new rules) at the time they were adopted, while other

firms had to increase the number of independent directors after the rules came into effect.

We classify these banks as being affected by the reform. We then examine the change in

our two risk measures for the affected and non-affected banks following the adoption of

the reforms.9 To do this, we create a Post dummy variable that takes on a value of one for

the time period after the implementation of reforms starting in 2004, and we interact it

with an Affected dummy variable, indicating whether a bank was affected by the reforms.

In our sample, about 12% of banks were affected by the new rules, as seen in Panel B of

Table 2 with summary statistics.10 The interaction of the Post and Affected variables is

included in Z-score and distance to default regressions to ascertain whether the forced

increase in board independence on account of the new regulations caused an increase in

bank insolvency risk. The results are reported as regressions 5 and 6 in Table 10. In both

7 Several papers have used the introduction of NYSE and NASDAQ rules requiring majority board

independence, and the Sarbanes-Oxley regulations requiring majority independence in the audit committee

as exogenous shocks to governance. See, for instance, Duchin, Matsusaka and Ozbas (2010), Chhaochharia

and Grinstein (2009), Linck, Netter and Yang (2008), and Armstrong, Core and Guay (2014). 8 NYSE-listed and NASDAQ-listed firms were required to implement the new requirement by their first

annual meeting occurring after January 15, 2004, but no later than October 31, 2004 and October 15, 2004,

respectively. 9 We obtain similar results using an instrumental variables approach to changes in the share of independent

directors from 2000 to 2004 as in Duchin, Matsusaka and Ozbas (2010) (unreported). 10 Consistent with Armstrong, Core and Guay (2014), we find that initially non-compliant firms had a

significant increase in independent directors compared to initially compliant firms.

26

regressions, the interactions of Post and Affected variables have a negative and

significant coefficient, which suggests a causal effect of greater board independence on

bank insolvency risk.

Overall, the evidence in this section shows that bank insolvency risk varies more

positively with shareholder-friendly corporate governance for banks than for non-banks,

and that this effect is more pronounced for larger banks compared to larger non-bank

corporations. These results suggest a causal relationship between shareholder-friendly

corporate governance and insolvency risk. Further, we find that exogenous increases in

board independence of US banks following new regulations are positively related with

increases in bank insolvency risk as strong evidence of a causal link between

shareholder-friendly corporate governance and bank insolvency risk.

4. Conclusion

This paper provides evidence that more shareholder-friendly corporate

governance is associated with greater bank insolvency and systemic risks for an

international sample of banks. These empirical relationships are robust to including bank

fixed effects and instrumental variable estimation, alleviating endogeneity concerns. We

further find that ‘good’ corporate governance is associated with increased asset volatility,

more non-performing loans, and a lower tangible equity ratio.

Our findings that ‘good’ corporate governance is associated with increased risk

taking at financial firms are consistent with earlier research showing that better investor

protection reduces excessive risk-avoidance at non-financial firms explained by the fact

that managers earn private benefits from reducing risk. Banks, however, are special in

27

that they benefit from the financial safety net. The financial safety net provides banks

with an incentive to take on too much risk, as banks receive financial support from the

financial safety if they become distressed.

This suggests that risk taking at banks is determined by the interaction of

corporate governance regimes and the financial safety net. We find empirical support for

this hypothesis by showing that ‘good’ corporate governance increases bank risk taking

especially for banks that are large and located in countries with generous financial safety

nets. For these banks, more risk can be expected to increase their contingent claim on the

financial safety net. ‘Good’ corporate governance thus reinforces the tendency for banks

to exploit the financial safety net, if they are in a position to do so.

For an international sample of banks and non-banks, we find that shareholder-

friendly corporate governance is more positively related to insolvency risk at banks than

at non-banks, especially in the case of large firms. This is further evidence of the special

nature of banks, giving rise to a stronger relationship between shareholder-friendly

corporate governance and risk taking than in the case of non-bank corporations.

For the case of the US, we further find that regulatory reform towards greater

board independence in the US approved in 2003 increased bank insolvency risk at banks

that were affected by this regulation, which is evidence indicating a causal link between

shareholder-friendly corporate governance and bank risk taking.

The interaction of corporate governance and the financial safety net in

determining bank insolvency and systemic risks has important implications for public

policy towards corporate governance at banks. In particular, the case for more

shareholder-friendly corporate governance at banks is much weaker than in the case of

28

non-financial firms. In the case of banks, particularly large ones, ‘better’ corporate

governance may only exacerbate the excessive risk taking resulting from the banks’

incentives to exploit the financial safety. This paper’s finding that regulation towards

greater board independence in the US increased the riskiness of the affected banks

provides suggestive evidence of this. In the second-best world where mispriced financial

safety nets and too-big-to-fail policies exist, ‘better’ corporate governance thus may

actually produce worse outcomes. To prevent this, a first priority should be regulatory

and safety net reform to address too-big-to-fail issues and reduce moral hazard leading to

excess risk taking of banks. After such reforms the case for ‘better’ corporate governance

at banks would become much stronger.

29

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32

Appendix

A1. Measures of Stand-alone risk, systemic risk and risk-shifting

We follow Hillegeist, Keating, Cram, and Lundstedt (2004) and Campbell,

Hilscher and Szilagyi (2008) in calculating Merton’s (1974) distance to default. The

market equity value of a company is modeled as a call option on the company’s assets:

𝑉𝐸 = 𝑉𝐴𝑒−𝑑𝑇𝑁(𝑑1) − 𝑋𝑒−𝑟𝑇𝑁(𝑑2) + (1 − 𝑒−𝑑𝑇)𝑉𝐴

𝑑1 =log (

𝑉𝐴

𝑋 ) + (𝑟 − 𝑑 +𝑠𝐴

2

2 ) 𝑇

𝑠𝐴√𝑇; 𝑑2 = 𝑑1 − 𝑠𝐴√𝑇

(A1)

where 𝑉𝐸 is the market value of a bank, 𝑉𝐴 is the value of the bank’s assets, X is the face

value of debt maturing at time T, r is the risk free rate, d is the dividend rate expressed in

terms of 𝑉𝐴, and where N(xi) is the probability that x ≤ xi given that x is distributed with

zero mean and unit variance. 𝑠𝐴 is the volatility of the value of assets, which is related to

equity volatility through the following equation:

𝑠𝐸 =

𝑉𝐴𝑒−𝑑𝑇 𝑁(𝑑1)𝑠𝐴

𝑉𝐸 (A2)

We simultaneously solve equations (A1) and (A2) to find the values of 𝑉𝐴 and 𝑠𝐴.

We use the market value of equity for 𝑉𝐸 and total liabilities to proxy for the face value

of debt, X. Since the accounting information is on an annual basis, we linearly interpolate

the values for all dates over the period, using end of year values for accounting items.

The interpolation method has the advantage of producing a smooth implied asset value

process and avoids jumps in the implied default probabilities at year end. 𝑠𝐸 is the

standard deviation of daily equity returns over the past 12 months. In calculating standard

33

deviations, we require the company to have at least 90 non-zero and non-missing returns

over the previous 12 months. T equals one year, and r is the one-year Treasury bill rate,

which we take to be the risk-free rate. The dividend rate, d, is the sum of the prior year’s

common and preferred dividends divided by the market value of assets. We use the

Newton method to simultaneously solve the two equations above. For starting values of

the unknown variables, we use VA = VE + X and sA = sEVE/(VE+X). After we determine

asset values VA, we follow Campbell, Hilscher and Szilagyi (2008) and assign asset return

m to be equal to the equity premium given by 6%.11 Merton’s (1974) distance to default

is finally computed as:

Distance to default =𝑙𝑜𝑔 (

𝑉𝐴

𝑋 ) + (𝑚 − 𝑑 −𝑠𝐴

2

2 ) 𝑇

𝑠𝐴√𝑇

(A3)

Following Hovakimian, Kane and Laeven (2003) and Bushman and Williams

(2012), we estimate IPP as the value of a put option on bank liabilities as follows:

IPP = 𝑁 (𝑙𝑜𝑔 (

𝑋𝑉𝐴

) +𝑠𝐴

2

2 𝑇

𝑠𝐴√𝑇) − (

𝑉𝐴

𝑋) 𝑁 (

𝑙𝑜𝑔 (𝑋𝑉𝐴

) −𝑠𝐴

2

2 𝑇

𝑠𝐴√𝑇) (A4)

In the empirical work, IPP is expressed as the value of the put option per dollar of

bank liabilities in cents.

11 We obtain similar distance to default values if we compute the asset return as max (

𝑉𝐴,𝑡

𝑉𝐴,𝑡−1−

1, 𝑟) following Hillegeist, Keating, Cram, and Lundstedt (2004).

34

Following Acharya et al. (2010), we compute Marginal Expected Shortfall (MES)

as the average bank equity return on days when the market as a whole is in the tail of its

loss distribution:

𝑀𝐸𝑆𝑡𝑖 = 𝐸(𝑅𝑖,𝑡 | 𝑅𝑚,𝑡 < 𝐶) (A5)

where 𝑅𝑖,𝑡 is bank i’s equity return, 𝑅𝑚,𝑡 is the aggregate market index return, and C is

the 5th percentile value of the market index return in the previous year. We use daily

stock returns from Compustat for non-US banks, and daily stock market information

from CRSP for US banks. For the aggregate market index, we use the stock index of the

country where the bank is incorporated. Daily country stock index data are from

Compustat Global.

In line with Adrian and Brunnermeier (2015), we compute the Covar measure for

each bank using quantile regressions and a set of macro state variables. In particular, we

run the following quantile regressions:

𝑅𝑖,𝑡 =∝𝑖+ 𝛾𝑖𝑀𝑡−1 + 휀𝑖,𝑡

𝑅𝑚,𝑡 =∝𝑠𝑦𝑠𝑡𝑒𝑚|𝑖+ 𝛽𝑠𝑦𝑠𝑡𝑒𝑚|𝑖 𝑅𝑖,𝑡 + 𝛾𝑠𝑦𝑠𝑡𝑒𝑚|𝑖𝑀𝑡−1 + 휀𝑠𝑦𝑠𝑡𝑒𝑚|𝑖,𝑡

(A6)

where 𝑅𝑖,𝑡 is the equity return for bank i in week t, 𝑅𝑚,𝑡 is the weekly value-weighted

return of all banks in a given country, and 𝑀𝑡−1 are lagged state variables (including the

change in the 3-months T-bill rate, the change in the term spread, the weekly country

stock index return, and the volatility of the daily country stock index return over the past

four weeks). We use weekly stock returns from Compustat Global for non-US banks, and

weekly stock market information from CRSP for US banks. For the aggregate market

index, we use the country stock index of the country where the bank is incorporated.

35

The Covar variable is computed as the change in the value at risk of the system

when the institution’ return is at the qth percentile (or when the institution is in distress)

minus the value at risk of the system when the institution’ return is at the 50% percentile:

Covar𝑡𝑞 = �̂�𝑠𝑦𝑠𝑡𝑒𝑚|𝑖

𝑞 (𝑅𝑖,𝑡�̂� − 𝑅𝑖,𝑡

50%̂) (A7)

We calculate the Covar measure at q=5% for each bank in our sample using data

for rolling three year periods in order to accommodate time varying business conditions

(Moore and Zhou 2011).

36

A2. Variable definitions, data sources, governance attributes, and country coverage

Table A1. Variable definitions and data sources

Variable name Definition Data source

Risk and return variables

Z-score Index of bank solvency constructed as the logarithm of (E(ROA) + CAR)/SROA where ROA is return

on assets, CAR represents capital assets ratio and SROA stands for standard deviation of return on assets.

Authors’ calculation

Distance to default Annual average of distance-to-default based on stock price variability Authors’ calculation

MES Average bank stock return when market return is in the lowest 5% bracket in a given year Authors’ calculation

CoVaR Value at risk of the financial system when a bank’s stock return is at the 5th percentile minus value of

risk of the financial system when a bank’s stock return is at the 50th percentile in a given year

Authors’ calculation

Asset volatility Annualized standard deviation of the asset return implicit in Merton’s option pricing model Authors’ calculation

Asset risk weight Risk weighted assets divided by total asset BankScope

Loans Loans divided by total assets BankScope

Non-performing loans Non-performing loans divided by gross loans outstanding BankScope

Non-interest income Share of non-interest income in total operating income BankScope

Tier 1 capital Tier 1 capital divided by risk weighted assets BankScope

Regulatory capital The sum of tier 1 and tier 2 capital divided by risk weighted assets BankScope

Tangible capital Ratio of tangible capital to tangible assets BankScope

Non-deposit funding Share of non-deposit short-term funding in total deposits and short-term funding BankScope

Asset growth Growth rate of total assets BankScope

Asset procyclicality Correlation coefficient between bank asset growth rate and GDP growth rate BankScope

Lending procyclicality Correlation coefficient between loan growth rate and GDP growth rate BankScope

NPL procyclicality Correlation coefficient between non-performing loan ratio and GDP growth rate BankScope

Tangible capital procyclicality Correlation coefficient between tangible capital ratio and GDP growth rate BankScope

Governance variables

Corporate governance Overall corporate governance index ISS

Board Corporate governance index based on board characteristics ISS

Compensation and ownership Corporate governance index based on compensation and ownership characteristics ISS

Auditing Corporate governance index based on auditing characteristics ISS

Takeover Corporate governance index based on takeover characteristics ISS

Affected Dummy variable that equals one for US banks that had fewer than 50% independent board members in

2002

ISS

Firm control variables

Assets Logarithm of total assets BankScope

Assets to GDP Total assets divided by GDP BankScope

Overhead Overhead divided by total assets BankScope

Collateral Assets that can be used as collateral (securities, cash and due from other banks, and fixed assets) divided

by total assets

BankScope

37

Book-to-market Book value of total equity divided by the market value of total equity CRSP, Compustat North

America, and Compustat

Global

ROA Operating income divided by total assets BankScope and Compustat

North America, and

Compustat Global

Macro and institutional control variables

Financial safety net Sum of first four principal components with an eigenvalue exceeding one based on 8 deposit insurance

scheme design features as follows: (1) coverage of foreign currency deposits, (2) coverage of interbank

deposits, (3) an absence of coinsurance, (4) coverage per depositor per bank per account, (5) funded ex

ante, (6) funded by government, (7) risk-insensitive insurance premium, (8) the ratio of insurance

coverage and deposits per capita, with a higher value for each feature suggesting a more generous

financial safety net and more severe moral hazard

Authors’ calculations based

on deposit insurance data in

year 2003 from Demirguc-

Kunt, Karacaovali and

Laeven (2005)

Inflation Consumer price inflation rate World Development

Indicators

GDP growth Rate of real GDP growth World Development

Indicators

GDP per capita GDP per capita in thousands of constant 2005 U.S. dollars World Development

Indicators

Restrict Index of regulatory restrictions on bank activities Barth, Caprio and Levine

(2004)

Capital stringency Index of regulatory oversight of bank with higher values indicate greater stringency Barth, Caprio and Levine

(2004)

Official Index of power of commercial bank supervisory agency. It measures the power of the supervisory

authorities to take specific actions to prevent and correct problems with higher values indicating greater

power.

Barth, Caprio and Levine

(2004)

Diversification Index of diversification guidelines imposed on banks with higher values indicating more diversification. Barth, Caprio and Levine

(2004)

Financial freedom Index of financial freedom with higher values indicating greater freedom. Heritage Foundation

38

Table A2. Corporate governance attributes

Board attributes

1. All directors attended 75% of board meetings or had a valid excuse

2. CEO serves on the boards of two or fewer public companies

3. Board is controlled by more than 50% independent outside directors

4. Board size is greater than 5 but less than 16

5. CEO is not listed as having a related-party transaction

6. No former CEO on the board

7. Compensation committee composed solely of independent outsiders

8. Chairman and CEO are separated or there is a lead director

9.Nominating committee composed solely of independent outsiders

10.Governance committee exists and met in the past year

11.Shareholders vote on directors selected to fill vacancies

12.Governance guidelines are publicly disclosed

13.Annually elected board (no staggered board)

14.Policy exists on outside directorships (four or fewer boards is the limit)

15.Shareholders have cumulative voting rights

16.Shareholder approval is required to increase/decrease board size

17.Majority vote requirement to amend charter/bylaws

18.Board has the express authority to hire its own advisors

19.Performance of the board is reviewed regularly

20.Board-approved succession plan in place for the CEO

21.Outside directors meet without CEO and disclose number of times met

22.Directors are required to submit resignation upon a change in job

23.Board cannot amend bylaws without shareholder approval or can do so only under limited circumstances

24.Does not ignore shareholder proposal

25.Qualifies for proxy contest defenses combination points

Compensation and ownership attributes

26.Directors are subject to stock ownership requirements

27.Executives are subject to stock ownership guidelines

28.No interlocks among compensation committee members

29.Directors receive all or a portion of their fees in stock

30.All stock-incentive plans adopted with shareholder approval

31.Options grants align with company performance and reasonable burn rate

32.Company expenses stock options

33.All directors with more than one year of service own stock

34.Officers' and directors' stock ownership is at least 1% but not over 30% of total shares outstanding

35.Repricing is prohibited

Auditing attributes

36.Board independence: Audit committee

37.Consulting fees paid to auditors are less than audit fees paid to auditors

38.Auditors ratified at most recent annual meeting

Antitakeover attributes

39.Single class, common

40.Majority vote requirement to approve mergers (not supermajority)

41.Shareholders may call special meetings

42.Shareholder may act by written consent

43.Company either has no poison pill or a pill that was shareholder approved

44.Company is not authorized to issue blank check preferred

Source: Aggarwal et al. (2009)

39

Table A3. Country coverage

Country name Frequency Percent

Australia 35 1.14

Austria 8 0.26

Belgium 18 0.59

Canada 44 1.44

Denmark 8 0.26

France 14 0.46

Germany 38 1.24

Greece 26 0.85

Hong Kong 44 1.44

Ireland 15 0.49

Italy 41 1.34

Japan 264 8.61

Korea Republic of 2 0.07

Netherlands 15 0.49

Norway 2 0.07

Portugal 15 0.49

Singapore 19 0.62

Spain 18 0.59

Sweden 20 0.65

Switzerland 20 0.65

United Kingdom 65 2.12

United States 2,334 76.15

40

Table 1. Summary statistic for the international sample of banks Z-score is an index of bank solvency constructed as the logarithm of (E(ROA) + CAR)/SROA where ROA

is return on assets and CAR represents capital assets ratio and SROA is standard deviation of the return on

assets. Distance to default is the annual average of distance to default based on stock price variability. MES

is average bank stock return when market return is in the lowest 5% bracket in a given year. CoVaR is

value at risk of the financial system when a bank’s stock return is at the 5th percentile minus value of risk

of the financial system when a bank’s stock return is at the 50th percentile in a given year. Asset volatility

is the annualized standard deviation of the asset return implied by Merton’s option pricing model. Asset

risk weight is risk weighted assets divided by total assets. Loans is the ratio of loans to total bank assets.

Non-performing loans is the fraction of non-performing loans in gross loan outstanding. Non-interest

income is the share of non-interest income in total operating income. Tier 1 capital is tier 1 capital divided

by risk weighted assets. Regulatory capital is the sum of tier 1 and tier 2 capital divided by weighted assets.

Tangible capital is tangible capital divided by total assets. Non-deposit funding is the share of non-deposit

short-term funding in total deposits and short-term funding. Asset growth is the growth rate of total assets.

Asset procyclicality is the correlation coefficient between asset growth and GDP growth. Lending

procyclicality is the correlation coefficient between loan growth and GDP growth. NPL procyclicality is the

correlation coefficient non-performing loans as a fraction of total loans outstanding and GDP growth.

Tangible capital procyclicality is the correlation coefficient between the tangible capital ratio and GDP

growth. Corporate governance is an overall corporate governance index. Board is an index of corporate

governance based on board characteristics. Compensation and ownership is an index of corporate

governance based on compensation and ownership characteristics. Auditing is an index of corporate

governance based on auditing characteristics. Takeover is an index of corporate governance based on

takeover characteristics. Assets is the logarithm of total assets. Financial safety net is the sum of first four

principal components with an eigenvalue exceeding one based on a range of deposit insurance design

features with a higher value for each feature suggesting a more generous financial safety net. Assets to

GDP is total assets divided by GDP. Overhead is overhead divided by total assets. Collateral is assets that

can easily be used as collateral divided by total assets. Inflation is the consumer price inflation rate. GDP

growth is the rate of real GDP growth. GDP per capita is GDP per capita in thousands of constant U.S.

dollars. Restrict is an index of regulatory restrictions on bank activities. Capital stringency is an index of

regulatory oversight of bank capital with higher values indicate greater stringency. Official is an index of

power of commercial bank supervisory agency. It measures the power of the supervisory authorities to take

specific actions to prevent and correct problems with higher values indicating greater power.

Diversification is an index of diversification guidelines imposed on banks with higher values indicating

more diversification. Financial freedom is an index of financial freedom with higher values indicating

greater freedom.

Variable Obs Mean Std. dev. Min Max

Z-score 3017 4.0387 1.2408 -7.6043 8.5504

Distance to default 2868 6.0332 2.0827 1.2493 12

MES 3069 -0.0206 0.0261 -0.2404 0.4612

CoVaR 3057 -0.0404 0.0410 -0.3008 0.0601

Asset volatility 3077 0.0474 0.0332 0.0017 0.3752

Asset risk weight 2260 0.7007 0.1531 0.0712 0.9988

Loans 3077 0.7038 0.1984 0 1

Non-performing loans 2793 0.0140 0.0188 0 0.1

Non-interest income 2965 0.2928 0.2006 0 1

Tier 1 capital 2297 0.1113 0.0343 0 0.3916

41

Regulatory capital 2315 0.1303 0.0306 0 0.3717

Tangible capital 3024 0.0725 0.0378 0 0.3982

Non-deposit funding 3063 0.1680 0.2545 0 1.0031

Asset growth 3084 0.0596 0.1233 -0.6931 0.6848

Asset procyclicality 697 0.1312 0.3908 -0.9053 0.9918

Lending procyclicality 684 0.2004 0.4065 -0.9630 0.9870

NPL procyclicality 620 -0.3762 0.3505 -0.9915 0.9471

Tangible capital procyclicality 682 0.1814 0.3797 -0.9487 0.9742

Corporate governance 3017 0.5975 0.0866 0.3333 0.8649

Board 3017 0.5341 0.1137 0.2500 0.9091

Compensation and ownership 3017 0.6888 0.1590 0 1

Auditing 3017 0.7296 0.2590 0 1

Takeover 3017 0.6308 0.1993 0 1

Financial safety net index 2839 3.9044 2.1480 -4.5400 4.8798

Assets 3017 8.4123 2.2562 3.4965 14.8571

Assets to GDP 3017 0.0608 0.2417 0.0000 2.6834

Overhead 3017 0.0324 0.0453 0.0009 0.7992

Collateral 3017 0.2682 0.1496 0.0051 0.9978

Inflation 3017 0.0249 0.0098 -0.0250 0.0488

GDP growth 3017 0.0277 0.0099 -0.0091 0.0916

GDP per capita 3017 40.5219 4.5401 17.9529 67.8046

Restrict 3017 7.6586 1.0935 3 9

Capital stringency 3017 4.9549 0.6244 2 8

Official 3017 12.4054 1.5301 5 14

Diversification 3017 1.4611 0.5104 0 2

Financial freedom 3017 81.8794 15.5070 30 90

42

Table 2. Summary statistics for international sample of bank and non-banks, and

sample of US banks Z-score is an index of bank solvency constructed as the logarithm of (E(ROA) + CAR)/SROA where ROA

is return on assets and CAR represents capital assets ratio and SROA is standard deviation of the return on

assets. Distance to default is the annual average of distance to default based on stock price variability.

Assets is the logarithm of total assets. Book-to-market is the book value of total equity divided by the

market value of total equity. ROA is the return on assets. Bank is a dummy is variable that equals one for

firms classified as banks or diversified financials by ISS, and zero otherwise. Corporate governance is an

overall corporate governance index. Post is a dummy variable that equals one for the years 2004-2006, and

zero otherwise. Affected is a dummy variable that equals one for banks that had fewer than 50%

independent board members in 2002. Panel A reports summary statistics for the sample of banks and non-

banks globally in the period 2004-2008 used in regressions 1-4 of Table 10. Panel B reports summary

statistics for the sample of banks in the period 2000-2005 used in regressions 5-6 of Table 10.

Panel A: International sample of banks and non-banks in 2004-2008

Variable Obs Mean Std. dev. Min Max

Z-score 27937 3.057 1.505 -8.617 6.262

Distance to default 28956 5.676 2.758 -5.988 32.960

Assets 32180 6.716 2.329 -3.170 15.146

Book-to-market 24603 3.030 3.219 0.440 22.813

ROA 31587 0.007 0.148 -0.969 0.289

Bank 32180 0.139 0.346 0.000 1.000

Corporate governance 32180 0.612 0.093 0.297 0.952

Panel B: Sample of US banks in 2000-2005

Variable Obs Mean Std. dev. Min Max

Z-score 523 4.161 1.042 1.002 6.231

Distance to default 563 6.404 1.827 -0.276 11.666

Assets 565 9.905 1.595 5.513 14.449

Book-to-market 563 2.370 1.026 0.227 8.961

ROA 565 0.014 0.015 -0.073 0.152

Affected 472 0.121 0.316 0.000 1.000

43

Table 3. Bank risk and corporate governance The dependent variables in the four columns are Z-score, distance to default, MES, and CoVaR. Z-score is

an index of bank solvency constructed as the logarithm of (E(ROA) + CAR)/SROA where ROA is return

on assets and CAR represents capital assets ratio and SROA is standard deviation of the return on assets.

Distance to default is the annual average of distance to default based on stock price variability. MES is

average bank stock return when market return is in the lowest 5% bracket in a given year. CoVaR is value

at risk of the financial system when a bank’s stock return is at the 5th percentile minus value of risk of the

financial system when a bank’s stock return is at the 50th percentile in a given year. Assets is the logarithm

of total assets. Assets to GDP is total assets divided by GDP. Overhead is overhead divided by total assets.

Collateral is assets that can easily be used as collateral divided by total assets. Inflation is the consumer

price inflation rate. GDP growth is the rate of real GDP growth. GDP per capita is GDP per capita in

thousands of constant U.S. dollars. Restrict is an index of regulatory restrictions on bank activities. Capital

stringency is an index of regulatory oversight of bank capital with higher values indicate greater stringency.

Official is an index of power of commercial bank supervisory agency. It measures the power of the

supervisory authorities to take specific actions to prevent and correct problems with higher values

indicating greater power. Diversification is an index of diversification guidelines imposed on banks with

higher values indicating more diversification. Financial freedom is an index of financial freedom with

higher values indicating greater freedom. Corporate governance is an overall corporate governance index.

Board is an index of corporate governance based on board characteristics. Compensation and ownership is

an index of corporate governance based on compensation and ownership characteristics. Auditing is an

index of corporate governance based on auditing characteristics. Takeover is an index of corporate

governance based on takeover characteristics. Regressions include bank and year fixed effects. Regressions

in Panel A include the corporate governance variable. Regressions in Panel B include the Board,

Compensation and ownership, Auditing and Takeover variables. Regressions in Panel B include unreported

control variables. The sample consists of banks internationally. Regressions include bank and year fixed

effects. Standard errors are clustered at the bank level, and provided in parentheses. *, **, and *** denote

significance at 10%, 5%, and 1%, respectively.

Z-score

(1)

Distance to default

(2)

MES

(3)

CoVaR

(4)

Assets -0.578*** -0.081 -0.009* -0.014***

(0.193) (0.219) (0.005) (0.005)

Assets to GDP -1.262* -0.650 -0.028 0.038

(0.647) (0.820) (0.020) (0.027)

Overhead -1.258 -3.037 -0.065 0.000

(2.639) (2.805) (0.068) (0.108)

Collateral -0.366 -0.289 -0.003 0.018

(0.470) (0.581) (0.011) (0.014)

Inflation -0.213 -4.588 0.386*** 0.407**

(8.318) (12.636) (0.132) (0.196)

GDP growth 16.431*** 25.309*** 0.462*** 0.431***

(4.889) (9.080) (0.148) (0.134)

GDP per capita -0.212** -0.181 -0.004** 0.000

(0.093) (0.138) (0.002) (0.003)

Restrict 0.048 -0.416** -0.003 0.004

(0.135) (0.177) (0.005) (0.003)

Capital stringency -0.047 0.130 0.001 -0.003

(0.088) (0.104) (0.003) (0.003)

Official 0.009 -0.036 -0.001 -0.000

(0.042) (0.052) (0.001) (0.002)

Diversification 0.578*** -0.693*** -0.001 0.004*

(0.117) (0.123) (0.002) (0.002)

Financial freedom 0.013** 0.019*** -0.000*** -0.000

(0.005) (0.007) (0.000) (0.000)

Corporate governance -0.832* -1.453** -0.042*** -0.044***

(0.503) (0.595) (0.009) (0.014)

N 3017 2868 3069 3057

adj. R-sq 0.210 0.557 0.458 0.478

Bank fixed effects Yes Yes Yes Yes

44

Year fixed effects Yes Yes Yes Yes

Panel B

Board -0.618 -1.237*** -0.009 -0.011

(0.411) (0.474) (0.007) (0.010)

Compensation and ownership 0.071 -0.474 -0.017*** -0.012**

(0.198) (0.311) (0.005) (0.006)

Auditing -0.174 0.148 -0.002 -0.004

(0.124) (0.149) (0.002) (0.003)

Takeover 0.344 0.070 -0.016*** -0.022**

(0.320) (0.347) (0.006) (0.010)

N 3017 2868 3069 3057

adj. R-sq 0.211 0.558 0.460 0.479

Bank fixed effects Yes Yes Yes Yes

Year fixed effects Yes Yes Yes Yes

45

Table 4. Bank risk, size, and corporate governance The dependent variables in the four columns are Z-score, distance to default, MES, and CoVaR. Z-score is

an index of bank solvency constructed as the logarithm of (E(ROA) + CAR)/SROA where ROA is return

on assets and CAR represents capital assets ratio and SROA is standard deviation of the return on assets.

Distance to default is the annual average of distance to default based on stock price variability. MES is

average bank stock return when market return is in the lowest 5% bracket in a given year. CoVaR is value

at risk of the financial system when a bank’s stock return is at the 5th percentile minus value of risk of the

financial system when a bank’s stock return is at the 50th percentile in a given year. Assets is the logarithm

of total assets. Assets to GDP is total assets divided by GDP. Overhead is overhead divided by total assets.

Collateral is assets that can easily be used as collateral divided by total assets. Inflation is the consumer

price inflation rate. GDP growth is the rate of real GDP growth. GDP per capita is GDP per capita in

thousands of constant U.S. dollars. Restrict is an index of regulatory restrictions on bank activities. Capital

stringency is an index of regulatory oversight of bank capital with higher values indicate greater stringency.

Official is an index of power of commercial bank supervisory agency. It measures the power of the

supervisory authorities to take specific actions to prevent and correct problems with higher values

indicating greater power. Diversification is an index of diversification guidelines imposed on banks with

higher values indicating more diversification. Financial freedom is an index of financial freedom with

higher values indicating greater freedom. Corporate governance is an overall corporate governance index.

The sample consists of banks internationally. Regressions include bank and year fixed effects. Standard

errors are clustered at the bank level, and provided in parentheses. *, **, and *** denote significance at

10%, 5%, and 1%, respectively.

Z-score

(1)

Distance to default

(2)

MES

(3)

CoVaR

(4)

Assets -1.307** -0.095 -0.012 0.056**

(0.651) (0.842) (0.021) (0.028)

Assets to GDP -1.284 -2.801 -0.060 0.007

(2.650) (2.789) (0.068) (0.106)

Overhead -0.376 -0.179 -0.000 0.021

(0.472) (0.581) (0.011) (0.014)

Collateral 16.296*** 26.428*** 0.519*** 0.489***

(4.889) (9.243) (0.156) (0.141)

Inflation -0.210** -0.206 -0.005*** -0.001

(0.093) (0.139) (0.002) (0.003)

GDP growth -0.251 -3.365 0.443*** 0.498***

(8.322) (12.661) (0.129) (0.192)

GDP per capita 0.050 -0.444** -0.004 0.003

(0.136) (0.179) (0.005) (0.003)

Restrict -0.049 0.159 0.002 -0.002

(0.088) (0.105) (0.003) (0.003)

Capital stringency 0.011 -0.058 -0.002* -0.001

(0.043) (0.053) (0.001) (0.002)

Official 0.575*** -0.656*** 0.000 0.005**

(0.117) (0.124) (0.002) (0.002)

Diversification 0.013** 0.020*** -0.000*** -0.000

(0.005) (0.007) (0.000) (0.000)

Financial freedom -0.612*** 0.362 0.003 -0.000

(0.227) (0.271) (0.006) (0.006)

Corporate governance -1.347 5.036** 0.136*** 0.155***

(1.853) (2.232) (0.038) (0.058)

Corporate governance * Assets 0.059 -0.747*** -0.021*** -0.023***

(0.194) (0.257) (0.005) (0.007)

N 3017 2868 3069 3057

adj. R-sq 0.210 0.560 0.465 0.483

Bank fixed effects Yes Yes Yes Yes

Year fixed effects Yes Yes Yes Yes

46

Table 5. Bank risk, the financial safety net, and corporate governance The dependent variables in the four columns are Z-score, distance to default, MES, and CoVaR. Z-score is

an index of bank solvency constructed as the logarithm of (E(ROA) + CAR)/SROA where ROA is return

on assets and CAR represents capital assets ratio and SROA is standard deviation of the return on assets.

Distance to default is the annual average of distance to default based on stock price variability. MES is

average bank stock return when market return is in the lowest 5% bracket in a given year. CoVaR is value

at risk of the financial system when a bank’s stock return is at the 5th percentile minus value of risk of the

financial system when a bank’s stock return is at the 50th percentile in a given year. Assets is the logarithm

of total assets. Assets to GDP is total assets divided by GDP. Overhead is overhead divided by total assets.

Collateral is assets that can easily be used as collateral divided by total assets. Inflation is the consumer

price inflation rate. GDP growth is the rate of real GDP growth. GDP per capita is GDP per capita in

thousands of constant U.S. dollars. Restrict is an index of regulatory restrictions on bank activities. Capital

stringency is an index of regulatory oversight of bank capital with higher values indicate greater stringency.

Official is an index of power of commercial bank supervisory agency. It measures the power of the

supervisory authorities to take specific actions to prevent and correct problems with higher values

indicating greater power. Diversification is an index of diversification guidelines imposed on banks with

higher values indicating more diversification. Financial freedom is an index of financial freedom with

higher values indicating greater freedom. Corporate governance is an overall corporate governance index.

Financial safety net is the sum of first four principal components with an eigenvalue exceeding one based

on a range of deposit insurance design features, with a higher value for each feature suggesting a more

generous financial safety net. The sample consists of banks internationally. Regressions include bank and

year fixed effects. Standard errors are clustered at the bank level, and provided in parentheses. *, **, and

*** denote significance at 10%, 5%, and 1%, respectively.

Z-score

(1)

Distance to default

(2)

MES

(3)

CoVaR

(4)

Assets -0.532* 0.455 -0.004 -0.014

(0.311) (0.442) (0.005) (0.010)

Assets to GDP -2.839*** -0.681 -0.014 0.090***

(0.838) (1.369) (0.015) (0.030)

Overhead -3.412 -2.935 -0.083 -0.012

(2.828) (2.973) (0.069) (0.119)

Collateral -0.515 -0.314 0.000 0.021

(0.484) (0.593) (0.010) (0.014)

Inflation -2.013 19.573 0.350* 0.412

(12.243) (23.549) (0.183) (0.328)

GDP growth 10.546* 34.004*** 0.381*** 0.886***

(6.230) (11.862) (0.086) (0.129)

GDP per capita -0.071 -0.290 -0.007*** -0.014***

(0.121) (0.208) (0.002) (0.004)

Restrict -0.183 -0.701** -0.001 -0.002

(0.205) (0.310) (0.002) (0.003)

Capital stringency 0.045 0.259 -0.001 -0.002

(0.140) (0.220) (0.002) (0.002)

Official -0.039 -0.143 -0.003*** 0.001

(0.063) (0.096) (0.001) (0.002)

Diversification 0.715*** -0.631*** -0.008*** -0.007**

(0.192) (0.207) (0.002) (0.003)

Financial freedom 0.015*** 0.011 -0.000*** -0.000**

(0.006) (0.009) (0.000) (0.000)

Corporate governance -8.648 6.895 0.055 0.261**

(5.460) (9.406) (0.087) (0.122)

Corporate governance * Assets 0.763 -0.681 -0.007 -0.027**

(0.482) (0.764) (0.008) (0.011)

Financial safety net * Assets 0.012 0.155 0.003*** 0.006**

(0.070) (0.097) (0.001) (0.002)

Corporate governance * Financial safety net 2.002* 1.108 0.049** 0.017

(1.179) (1.949) (0.020) (0.028)

Corporate governance * Financial safety net * Assets -0.215** -0.233 -0.007*** -0.005*

47

(0.110) (0.162) (0.002) (0.003)

N 2839 2701 2881 2869

adj. R-sq 0.214 0.563 0.573 0.500

Bank fixed effects Yes Yes Yes Yes

Year fixed effects Yes Yes Yes Yes

48

Table 6. Bank risk and corporate governance: IV estimation The dependent variables in the four columns are Z-score, distance to default, MES, and CoVaR. Z-score is

an index of bank solvency constructed as the logarithm of (E(ROA) + CAR)/SROA where ROA is return

on assets and CAR represents capital assets ratio and SROA is standard deviation of the return on assets.

Distance to default is the annual average of distance to default based on stock price variability. MES is

average bank stock return when market return is in the lowest 5% bracket in a given year. CoVaR is value

at risk of the financial system when a bank’s stock return is at the 5th percentile minus value of risk of the

financial system when a bank’s stock return is at the 50th percentile in a given year. Assets is the logarithm

of total assets. Assets to GDP is total assets divided by GDP. Overhead is overhead divided by total assets.

Collateral is assets that can easily be used as collateral divided by total assets. Inflation is the consumer

price inflation rate. GDP growth is the rate of real GDP growth. GDP per capita is GDP per capita in

thousands of constant U.S. dollars. Restrict is an index of regulatory restrictions on bank activities. Capital

stringency is an index of regulatory oversight of bank capital with higher values indicate greater stringency.

Official is an index of power of commercial bank supervisory agency. It measures the power of the

supervisory authorities to take specific actions to prevent and correct problems with higher values

indicating greater power. Diversification is an index of diversification guidelines imposed on banks with

higher values indicating more diversification. Financial freedom is an index of financial freedom with

higher values indicating greater freedom. Corporate governance is an overall corporate governance index.

Corporate governance is instrumented by the average corporate governance of all non-financial firms in the

same country in the same year. The sample consists of banks internationally. Regressions include bank and

year fixed effects. Standard errors are clustered at the bank level, and provided in parentheses. *, **, and

*** denote significance at 10%, 5%, and 1%, respectively.

Z-score

(1)

Distance to default

(2)

MES

(3)

CoVaR

(4)

Assets -0.574*** -0.085 -0.009* -0.014***

(0.192) (0.229) (0.005) (0.005)

Assets to GDP -1.308** -0.391 -0.026 0.041

(0.646) (0.914) (0.020) (0.028)

Overhead -1.148 -3.333 -0.069 -0.000

(2.611) (2.875) (0.066) (0.106)

Collateral -0.363 -0.407 -0.003 0.018

(0.463) (0.620) (0.011) (0.014)

Inflation -0.846 -1.364 0.443*** 0.496**

(8.642) (12.833) (0.127) (0.218)

GDP growth 16.631*** 22.834** 0.450*** 0.412***

(4.948) (9.432) (0.144) (0.138)

GDP per capita -0.209** -0.188 -0.004** -0.000

(0.093) (0.140) (0.002) (0.003)

Restrict 0.057 -0.459*** -0.004 0.004

(0.135) (0.177) (0.005) (0.003)

Capital stringency -0.058 0.182* 0.002 -0.002

(0.088) (0.102) (0.003) (0.003)

Official 0.014 -0.063 -0.002 -0.001

(0.044) (0.058) (0.001) (0.002)

Diversification 0.537*** -0.493*** 0.001 0.006**

(0.133) (0.159) (0.003) (0.003)

Financial freedom 0.012** 0.022*** -0.000*** -0.000

(0.005) (0.007) (0.000) (0.000)

Corporate governance 0.157 -6.599** -0.092** -0.111**

(1.542) (2.702) (0.043) (0.046)

N 2944 2789 2978 2968

adj. R-sq 0.213 0.538 0.454 0.475

Bank fixed effects Yes Yes Yes Yes

Year fixed effects Yes Yes Yes Yes

49

Table 7. Channels through which corporate governance can affect bank risk: asset

and income choices The dependent variables in the five columns are asset volatility, asset risk weight, loans, non-performing

loans, and non-interest income, respectively. Asset volatility is the annualized standard deviation of the

asset return implied by Merton’s option pricing model. Asset risk weight is risk weighted assets divided by

total assets. Loans is the ratio of loans to total bank assets. Non-performing loans is the fraction of non-

performing loans in gross loan outstanding. Non-interest income is the share of non-interest income in total

operating income. Assets is the logarithm of total assets. Assets to GDP is total assets divided by GDP.

Overhead is overhead divided by total assets. Collateral is assets that can easily be used as collateral

divided by total assets. Inflation is the consumer price inflation rate. GDP growth is the rate of real GDP

growth. GDP per capita is GDP per capita in thousands of constant U.S. dollars. Restrict is an index of

regulatory restrictions on bank activities. Capital stringency is an index of regulatory oversight of bank

capital with higher values indicate greater stringency. Official is an index of power of commercial bank

supervisory agency. It measures the power of the supervisory authorities to take specific actions to prevent

and correct problems with higher values indicating greater power. Diversification is an index of

diversification guidelines imposed on banks with higher values indicating more diversification. Financial

freedom is an index of financial freedom with higher values indicating greater freedom. Corporate

governance is an overall corporate governance index. The sample consists of banks internationally.

Regressions include bank and year fixed effects. Standard errors are clustered at the bank level, and

provided in parentheses. *, **, and *** denote significance at 10%, 5%, and 1%, respectively.

Asset

volatility

(1)

Asset risk

weight

(2)

Loans

(3)

Non-

performing

loans

(4)

Non-interest

income

(5)

Assets -0.021*** -0.046*** -0.007 0.014*** -0.027*

(0.005) (0.011) (0.010) (0.003) (0.015)

Assets to GDP 0.006 -0.003 0.070 -0.000 -0.038

(0.014) (0.046) (0.051) (0.009) (0.057)

Overhead 0.270 0.476** 0.359 0.075 0.732***

(0.165) (0.228) (0.390) (0.073) (0.257)

Collateral -0.001 -0.278*** -0.359*** 0.005 0.008

(0.015) (0.027) (0.062) (0.011) (0.036)

Inflation -0.077 0.281 0.556 0.080 -0.967

(0.264) (0.336) (0.508) (0.144) (0.631)

GDP growth -0.515*** 0.214 -0.220 -0.488*** -0.588

(0.116) (0.311) (0.334) (0.066) (0.369)

GDP per capita 0.003 0.006 0.007 -0.004** 0.002

(0.002) (0.005) (0.006) (0.002) (0.008)

Restrict -0.001 0.025*** 0.011 0.000 -0.014*

(0.003) (0.008) (0.008) (0.002) (0.007)

Capital stringency 0.001 -0.003 -0.002 0.000 0.007

(0.002) (0.006) (0.006) (0.001) (0.007)

Official 0.003** -0.001 0.005 0.000 0.000

(0.001) (0.003) (0.004) (0.001) (0.003)

Diversification 0.006** -0.028*** -0.014** -0.010*** 0.012

(0.003) (0.006) (0.007) (0.002) (0.010)

Financial freedom -0.001*** -0.001*** 0.000 -0.000*** 0.000

(0.000) (0.000) (0.000) (0.000) (0.000)

Corporate governance 0.024*** 0.016 0.040 0.017*** -0.040

(0.009) (0.025) (0.029) (0.006) (0.035)

N 3077 2260 3077 2793 2965

adj. R-sq 0.193 0.253 0.250 0.314 0.063

Bank fixed effects Yes Yes Yes Yes Yes

Year fixed effects Yes Yes Yes Yes Yes

50

Table 8. Channels through which corporate governance can affect bank risk:

liability and growth choices The dependent variables in the five columns are tier 1 capital, regulatory capital, tangible capital, non-

deposit funding, and asset growth. Tier 1 capital is tier 1 capital divided by risk weighted assets. Regulatory

capital is the sum of tier 1 and tier 2 capital divided by weighted assets. Tangible capital is tangible capital

divided by total assets. Non-deposit funding is the share of non-deposit short-term funding in total deposits

and short-term funding. Asset growth is the growth rate of total assets. Assets is the logarithm of total

assets. Assets to GDP is total assets divided by GDP. Overhead is overhead divided by total assets.

Collateral is assets that can easily be used as collateral divided by total assets. Inflation is the consumer

price inflation rate. GDP growth is the rate of real GDP growth. GDP per capita is GDP per capita in

thousands of constant U.S. dollars. Restrict is an index of regulatory restrictions on bank activities. Capital

stringency is an index of regulatory oversight of bank capital with higher values indicate greater stringency.

Official is an index of power of commercial bank supervisory agency. It measures the power of the

supervisory authorities to take specific actions to prevent and correct problems with higher values

indicating greater power. Diversification is an index of diversification guidelines imposed on banks with

higher values indicating more diversification. Financial freedom is an index of financial freedom with

higher values indicating greater freedom. Corporate governance is an overall corporate governance index.

The sample consists of banks internationally. Regressions include bank and year fixed effects. Standard

errors are clustered at the bank level, and provided in parentheses. *, **, and *** denote significance at

10%, 5%, and 1%, respectively.

Tier 1

capital

(1)

Regulatory

capital

(2)

Tangible

capital

(3)

Non-deposit

funding

(4)

Asset

growth

(5)

Assets -0.006 -0.003 -0.008** 0.023 -0.347***

(0.005) (0.005) (0.003) (0.015) (0.025)

Assets to GDP 0.030* 0.031 0.014 -0.030 0.161

(0.015) (0.019) (0.009) (0.053) (0.111)

Overhead 0.106 0.082 0.131 0.707** 0.222

(0.212) (0.221) (0.130) (0.354) (0.387)

Collateral 0.029** 0.023 -0.018 0.035 0.093

(0.015) (0.016) (0.011) (0.035) (0.072)

Inflation 0.011 -0.010 0.045 -0.388 -1.401

(0.132) (0.165) (0.077) (0.811) (1.073)

GDP growth 0.028 -0.096 0.083 -0.181 0.049

(0.121) (0.130) (0.075) (0.510) (0.522)

GDP per capita -0.005*** -0.004 -0.001 0.005 -0.018

(0.002) (0.002) (0.001) (0.010) (0.011)

Restrict -0.002 -0.004 0.001 -0.021* 0.008

(0.003) (0.003) (0.002) (0.011) (0.012)

Capital stringency 0.002 0.003 0.000 0.011 -0.027**

(0.002) (0.002) (0.001) (0.008) (0.010)

Official 0.000 0.000 -0.002** 0.002 -0.017***

(0.001) (0.001) (0.001) (0.004) (0.006)

Diversification 0.001 0.001 0.002 -0.003 0.007

(0.002) (0.002) (0.001) (0.006) (0.013)

Financial freedom 0.000*** 0.000*** 0.000 -0.000 -0.003***

(0.000) (0.000) (0.000) (0.000) (0.001)

Corporate

governance 0.004 -0.003 -0.015** 0.003 -0.023

(0.010) (0.012) (0.007) (0.029) (0.059)

N 2297 2315 3024 3063 3084

adj. R-sq 0.073 0.059 0.136 0.048 0.251

Bank fixed effects Yes Yes Yes Yes Yes

Year fixed effects Yes Yes Yes Yes Yes

51

Table 9. Banking procyclicality and corporate governance The dependent variables in column 1 is asset procyclicality which is the correlation coefficient between

asset growth and GDP growth. The dependent variables in column 2 is lending procyclicality which is the

correlation coefficient between loan growth and GDP growth. The dependent variables in column 3 is NPL

procyclicality which is the correlation coefficient between non-performing loans as a fraction of total loans

outstanding and GDP growth. The dependent variables in column 4 is tangible capital procyclicality which

is the correlation coefficient between the tangible capital ratio and GDP growth. Assets is the logarithm of

total assets. Assets to GDP is total assets divided by GDP. Overhead is overhead divided by total assets.

Collateral is assets that can easily be used as collateral divided by total assets. Inflation is the consumer

price inflation rate. GDP growth is the rate of real GDP growth. GDP per capita is GDP per capita in

thousands of constant U.S. dollars. Restrict is an index of regulatory restrictions on bank activities. Capital

stringency is an index of regulatory oversight of bank capital with higher values indicate greater stringency.

Official is an index of power of commercial bank supervisory agency. It measures the power of the

supervisory authorities to take specific actions to prevent and correct problems with higher values

indicating greater power. Diversification is an index of diversification guidelines imposed on banks with

higher values indicating more diversification. Financial freedom is an index of financial freedom with

higher values indicating greater freedom. Corporate governance is an overall corporate governance index.

The sample consists of banks internationally. Standard errors are robust to heteroskedasticity and provided

in parentheses. *, **, and *** denote significance at 10%, 5%, and 1%, respectively.

Asset procyclicality

(1)

Lending procyclicality

(2)

NPL procyclicality

(3)

Tangible capital

procyclicality

(4)

Assets 0.011 0.001 -0.015* -0.001

(0.010) (0.010) (0.008) (0.009)

Assets to GDP 0.195*** 0.140** -0.122** -0.084

(0.059) (0.065) (0.051) (0.082)

Overhead 0.578** 0.106 0.529 -0.464**

(0.246) (0.689) (0.634) (0.232)

Collateral -0.398*** -0.298** 0.427*** -0.121

(0.113) (0.145) (0.126) (0.111)

GDP growth -1.325 -3.756 5.853*** -6.881**

(2.870) (2.988) (2.089) (2.855)

Inflation 7.439** 17.038*** -19.988*** 9.402*

(3.606) (3.985) (4.352) (4.931)

GDP per capita 0.004 0.000 -0.003 0.008

(0.005) (0.005) (0.006) (0.006)

Restrict -0.057** -0.084*** 0.036 -0.094***

(0.028) (0.027) (0.030) (0.028)

Capital stringency -0.049** -0.062** -0.024 -0.081**

(0.024) (0.026) (0.026) (0.035)

Official 0.021 0.052*** -0.047*** 0.054***

(0.017) (0.017) (0.017) (0.017)

Diversification -0.030 -0.019 0.165* -0.096

(0.078) (0.075) (0.088) (0.098)

Financial freedom -0.006** -0.003 0.001 -0.005

(0.003) (0.003) (0.003) (0.003)

Corporate governance 0.145 0.138 -0.439*** -0.448**

(0.212) (0.224) (0.168) (0.222)

Observations 704 689 624 695

Adjusted R-squared 0.035 0.090 0.289 0.024

Bank fixed effects No No No No

Year fixed effects No No No No

52

Table 10. Banks and non-banks globally, and the impact of regulation on board independence in the US Z-score is an index of bank solvency constructed as the logarithm of (E(ROA) + CAR)/SROA where ROA is return on assets and CAR represents capital assets

ratio and SROA is standard deviation of the return on assets. Distance to default is the annual average of distance to default based on stock price variability.

Assets is the logarithm of total assets. Book-to-market is the book value of total equity divided by the market value of total equity. ROA is the return on assets.

Bank is a dummy is variable that equals one for firms classified as banks or diversified financials by ISS, and zero otherwise. Corporate governance is an overall

corporate governance index as described in the text. Post is a dummy variable that equals one for the years 2004-2006, and zero otherwise. Affected is a dummy

variable that equals one for banks that had fewer than 50% independent board members in 2002. Regressions 1-4 are for an international sample of banks and

non-banks for the time period 2004-2008. Regressions 5-6 are for a sample of US banks for the time period 2000-2005. Regressions 1-6 include firm fixed

effects, and regressions 1-4 include year fixed effects. Standard errors are clustered at the firm level, and provided in parentheses. *, **, and *** denote

significance at 10%, 5%, and 1%, respectively.

International sample of banks and non-banks US sample of banks

Z-score

Distance to

default Z-score

Distance to

default Z-score

Distance to

default

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

Assets 0.145*** -0.234*** 0.165** 0.186 0.529 -0.230

(0.046) (0.064) (0.070) (0.114) (0.464) (0.149)

Book-to-market -0.028*** 0.019** -0.028*** -0.017* 0.319*** 0.080

(0.006) (0.008) (0.006) (0.009) (0.112) (0.048)

ROA 2.313*** 2.255*** 2.317*** 2.029*** 4.316 5.840***

(0.131) (0.148) (0.131) (0.175) (10.069) (2.188)

Assets * Bank -0.555*** -0.396** -0.093 -0.018

(0.115) (0.195) (0.087) (0.114)

Book-to-market * Bank 0.181*** -0.060 0.192*** -0.120*

(0.046) (0.052) (0.048) (0.069)

ROA * Bank -0.240 0.882 -0.109 0.886

(0.836) (1.638) (0.778) (1.510)

Corporate governance 0.548** -0.294 0.905 7.932***

(0.221) (0.311) (0.635) (1.050)

Corporate governance * Bank -1.856*** -3.408*** 3.476*** 2.335

(0.502) (0.736) (1.285) (2.137)

Corporate governance * Assets -0.057 -1.343***

(0.089) (0.141)

Corporate governance * Assets * Bank -0.614*** -0.487*

(0.155) (0.259)

Post 1.799*** 0.197**

(0.192) (0.082)

Post * Affected -0.174* -0.432***

(0.102) (0.146)

53

N 21,763 24,158 21,763 22,694 487 455

adj. R-sq 0.730 0.848 0.730 0.821 0.699 0.770

Firm fixed effects Yes Yes Yes Yes Yes Yes

Year fixed effects Yes Yes Yes Yes No No

54

Figure 1. The corporate governance index for US and non-US banks, 2003-2007

.52

.54

.56

.58

.6.6

2

Me

an

2003 2004 2005 2006 2007Year

US banks Non-US banks