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Journal of Economics and Business 63 (2011) 456–471

Contents lists available at ScienceDirect

Journal of Economics and Business

CEO incentives and bank risk

James Cash Acrey∗, William R. McCumber, Thu Hien T. Nguyen

Department of Finance, Sam M. Walton College of Business, University of Arkansas, Fayetteville, AR 72701, United States

a r t i c l e i n f o

Article history:

Received 2 February 2010

Received in revised form 30 August 2010

Accepted 20 September 2010

JEL classification:

G01

G21

G32

J33

Keywords:

CEO compensation

Bank risk

Bank regulation

Bank failure

Bank

EDF

a b s t r a c t

We investigate the relationship between CEO compensation and

bank default risk predictors to determine if short-term incentives

can explain recent excesses in bank risk. We investigate early

warning off-site surveillance parameters and expected default fre-

quency (EDF) as well as crisis-related risky bank activities. We find

only modest evidence that CEO compensation structures promote

significant firm-specific heterogeneity in bank risk measures or

risky activities. Compensation elements commonly thought to be

the riskiest components, unvested options and bonuses, are eitherinsignificant or negatively correlated with common risk variables,

and only positively significant in predicting the level of trading

assets and securitization income.

© 2010 Elsevier Inc. All rights reserved.

1. Introduction and motivation

This economic crisis began as a financial crisis, when banks and financial institutions took huge,

reckless risks in pursuit of quick profits and massive bonuses. When the dust settled, and this

Special consideration should be given to this paper dueto the timeliness of bank reformlegislation and the growing popular

outcry about bank CEO composition. The data was collected from ExecuComp and Y9-C reports. The paper offers confirmation

of the Fahlenbrach and Stulz (2009) finding of incentive alignment between shareholders and bank CEOs, uses estimates of

bank default probabilities common to industry, and expands the literature on CEO compensation, bank CEO compensation,

bank specialness, bank failure, systemic banking risk, EDF, banking regulation, and agency theory.∗ Corresponding author. Tel.: +1 501 413 9047.

E-mail addresses: [email protected] (J.C. Acrey), [email protected] (W.R. McCumber),

[email protected] (T.H.T. Nguyen).

0148-6195/$ – see front matter © 2010 Elsevier Inc. All rights reserved.

doi:10.1016/j.jeconbus.2010.09.002

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J.C. Acrey et al. / Journal of Economics and Business 63 (2011) 456–471 457

binge of irresponsibility was over, several of the world’s oldest and largest financial institutions had

collapsed, or were on the verge of doing so (President Barack Obama, January 21, 2010).

Bank executives faced widespread criticism in the wake of the financial crisis for “privatizing gains

and socializing losses1. New York Attorney General Andrew Cuomo blasted the “Heads I Win, Tails

You Lose” culture of bank bonuses, claiming banks abuse the government’s safety net to captureupside gains without suffering downside losses because rapid compensation inflation during good

times remains high during periods of poor bank performance (Cuomo, 2009). Two dozen bank CEOs

collectively gained over $90 million in stock options during the crisis, further fueling public outrage

(Gomstyn, 2009).

The FDIC recently approved a policy to set deposit insurance premiums based, in part, on compen-

sation practice. At the time of this writing, Congress and the Obama administration are attempting to

force banks to dramatically change executive compensation. H.R. bill 3269 aims to align compensation

with long-term bank performance to reduce any preferences for short-term profits at the expense of

long-term bank solvency. The bill directs the Comptroller General of the United States to undertake

a rigorous study to “determine whether there is a correlation between compensation structures and

excessive risk taking” that contributed to the crisis. We motivate this research with the same objective.Arguments for regulating compensation to curtail bank risk-taking critically assume that CEO

compensation must drive bank risk. The contribution is by no means an established empirical fact.

Fahlenbrach and Stulz (2009) find no substantial evidence of agency problems during the financial

crisis that can be linked to bank CEO compensation. Gorton (2009) details complications in regulating

pay in a banking system increasingly dominated by shadow banking and pressured by a fiercely com-

petitive labor market. Levine (2004) advocates increased transparency to relieve regulators and allow

market discipline to punish overly aggressive risk-taking. This market-based narrative lends support

to those who blame regulators and government interference for the crisis.

We study the explanatory power of CEO compensation on common bank default risk measures

and, ex post , crisis-sensitive risky bank activities. We find only modest evidence that structural differ-

ences in bank CEO compensation, or any specific elements of CEO compensation, predict firm-specificheterogeneity in bank risk-taking activities. Our evidence lends support to the Fahlenbrach and Stulz

(2009) conclusion that CEO compensation was not a cause of the financial crisis and does not explain

bank risk.

The remainder of this paper proceeds as follows: Section 2 reviews the relevant literature. Section

3 develops our testable hypotheses. Section 4 describes our sample and defines our variables. Section

5 details our methodology. Section 6 reports our results. Section 7 concludes and offers avenues for

future research.

2. Literature review

Murphy (1999) claims that compensation plans should align the interests of risk-averse executives

with those of shareholders. Through a base salary, an annual bonus tied to accounting perfor-

mance, stock options, and long-term incentive plans (including restricted stock plans and multi-year

accounting-based performance plans), shareholders intend to compensate executives for their over-

investment of human capital in a single firm and their undiversified personal wealth portfolios. In

studying the financial crisis, Fahlenbrach and Stulz (2009) conclude that high levels of insider owner-

ship (the classic correction to the principal/agent incentive alignment problem) did not lead the banks

to take excessive risk. Bank CEOs suffered large losses during the crisis, indicating that while execu-

tives maintained well-aligned equity ownership stakes they may have misunderstood the accretion

of risk occurring within the banking system.

In contrast, Bebchuk and Spamann (2009) argue that the principal–agent conflict between bank

owners and managers has been effectively externalized to the taxpayers, and that compensation struc-

tures strongly determine the risk preferences of managers. Perhaps bank CEOs directed their firms into

1 Joseph Stiglitz, in various interviews with regard to his book, Freefall: America, Free Markets and the Sinking of the World

Economy, 2010.

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458 J.C. Acrey et al. / Journal of Economics and Business 63 (2011) 456–471

projects and business that shareholders valued and for which the CEOs were justly compensated. If

so, managerial interests were properly aligned with the risk appetites of their common shareholders.

One can argue that the truly “toxic tranche” of large bank equity ownership is implicitly held by the

taxpayers in the event of a systemic banking collapse. Jeitschko and Jeung (2005) model the moral

hazard of deposit insurance as an agency problem that increases managerial risk-taking incentives.

Houston and James (1995) report that bank CEO compensation policies promote risk-taking, as the

cash-to-equity compensation ratio in banking and financial services dominates cash compensation in

other industries. As bank risk increases, judged by an increasing proportion of non-interest income

sources, the proportion of equity-based CEO compensation also increases (Brewer, Hunter & Jackson,

2004).

Bryan, Hwang, and Lilien (2000) claim restricted stock fails to induce risk-averse CEOs to accept

riskier projects that should increase value. Clementi and Cooley (2009) find highly skewed compen-

sation measures, where many CEOs lose money due to the equity-based portion of their wealth,

reinforcing the notion that performance incentives have strengthened over time. Douglas (2006)

shows that value-maximizing compensation contracts induce bank managers to pursue riskier profits

from opaque investments with high levels of information asymmetry. During a financial crisis, the

opacity and complexity of assets become a liability when a firm needs to raise capital.As heated opinions motivate new bank regulation, market discipline advocates fault existing crisis-

inducing regulatory burdens. Palia (2000) warns that regulated industries attract CEO candidates with

lower education levels than deregulated industries. Thompson and Yan (1997) argue that Federal

Deposit Insurance Corporation Improvement Act regulation diminishes the effectiveness of private

executive compensation contracts.

Perhaps the most closely related literature to our study is a recent working paper by Cheng, Hong,

and Scheinkman (2009) examining total executive compensation (combining cash andequity pay) as it

impacts financial firm risk. They employ Murphy’s (2000) theory of irrelevance in the incentive effects

of cash and equity compensation. Our research compliments and extends this study ‘by separating the

components of bank CEO compensation. We incorporate a practitioner-oriented default risk measure,

a list of variables based on risky activities specific to the banking industry, and a view of risk whichexplicitly isolates the impact of short-term CEO incentives relative to the crisis. Our work utilizes

and expands threads on CEO compensation, bank risk and default risk, agency theory, and banking

regulation.

3. Hypothesis development

Does bank compensationincreasebank risk andfuela short-term bias? DidCEO compensationdrive

the risky behavior of banks leading to the financial crisis? We test the hypothesis that CEO compen-

sation motivates bank risk by seeking a significant correlation between bank risk and compensation

structures.We rely on a variety of risk measures used in credit analysis by regulators, banks and industry

analysts, and a subset of risky activities specifically related to the financial crisis. We decompose CEO

compensation into short-term and long-term components, and connect these to future risky activi-

ties undertaken by the bank. Our null hypothesis is that bank CEO compensation has no significantly

positive correlation to risky bank activities. We focus on publicly traded bank holding companies

(BHCs) in order to have meaningful comparisons of accounting data between firms; BHCs must file

quarterly reports with the Federal Reserve that include accounting and holdings data, including sup-

porting schedules and off balance-sheet items. We expect bonuses to positively correlate with risk

due to their explicit short-term performance focus. Salary is expected to be negatively correlated with

risk, as undue risk jeopardizes a CEO’s salary and continued employment. In optimal contracting the-

ory, fixed salaries satisfy the reservation wage, and the bonuses satisfy the incentive compatibilityconstraint. As both cash components are realized within the year, the comprehensive cash compensa-

tion package is expected to correlate positively with a short-term focus and risk-taking, with bonuses

dominating salary in influence. If CEOs did indeed take large risks in pursuit of big bonuses, bonuses

should be related positively and strongly to short-term performance and risk-taking.

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Our expectations of long-term incentives are more nuanced. Agency theory predicts that bank risk

should be an increasing function of equity holdings, if managers must be induced to take more risk

than they would without the incentive alignment offered by ownership (wealth effects from large

equity holdings, discussed below, may reduce a CEO’s risk appetite). Equity incentives are not meant

to promote excessive risk that jeopardizes the firm, though banks may be less bound by this constraint

if they exploit the safety net of insured deposits, or reasonably expect that the government will rescue

systemically important firms. CEO wealth is largely undiversified in own-firm equity. Vested equity

stakes should increase risk aversion via wealth protection effects, while unvested shares and options

should raise risk appetite through wealth accumulation effects (Agrawal & Mandelker, 1987). A CEO’s

ability to sell vested shares may attenuate this bias, but the market signaling effect of large insider

sales should dampen levels of CEO equity sales. We expect a negative impact on short-term risk due

to vested securities, and a positive impact from unvested shares and options.

4. Data definitions and summary statistics

4.1. Sample

Our study requires detailed compensation data for the largest banks in the U.S., those most likely

to pose systemic risk. We use Compustat’s ExecuComp database and searched for CEO compensation

data on all firms with SIC codes 6020–6029, 6080, 6081, 6082, 6090, 6199, 6712, and 6719. FR Y-9C

reports from the Chicago Federal Reserve provided bank accounting data. For the primary hypotheses

we focus on years 2004–2008. We use2-year lags of compensation variables to control for endogeneity

between contemporaneous risk and compensation.Our sample size for 2008(with2006 compensation

variables) is 84.

4.2. Independent variables – CEO compensation and control variables

CEO compensation variables are scaled by total compensation, which is defined as salary, bonus,

all other (perks), total value of restricted stock granted, total value of options granted, and long-

term incentivepayouts. Option values use the Black–Scholes–Merton methodology as per ExecuComp.

Variables are grouped by short-erm and long-term incentive structure; bonuses are incentives for

meeting short- to intermediate-term accounting measures goals, whereas vested shares should align

manager and shareholder incentives over the long term. Fig. 1 lists the variables used in our analysis

and their expected effects on firm risk.

Short-term compensation includes cash compensation components. We include an interactive

term, bonus interactive, which is the product of annual salary and bonus figures. We do this to capture

any marginal effects of high cash compensation. For example, salary or bonus may not be significantpredictors of bank risk, but the combination (high bonuses in the presence of high salary) may be

significant. Long-term compensation is divided into vested and unvested shares and options.

Table 1 reports summary statistics on the independent variables used in the study. Although all

of the firms in the study are large banking firms, there is considerable variation in how CEOs are

compensated. On one end of the spectrum, salary comprises nearly all of the compensation granted

to the CEO, while on the other end bonuses comprise almost 63% of total compensation. Interestingly,

relatively few banks award their CEOs bonuses at all; at the 50th percentile no bonuses are paid, and

at the 75th percentile, only 5% of the total compensation is in the form of bonuses. Vested long-term

cumulative compensation (vested shares and exercisable options) dwarfs the unvested wealth of bank

CEOs. At the means, vested shares are 13 times the value of unvested shares, and exercisable options

are worth 10 times the amount of un-exercisable options. This could significantly impact incentiveschemas, as CEOs may sell vested shares and exercisable options, reducing the alignment between

executive and shareholder interests. Since executives must report sales and exercised options, sending

a negative signal to the market, vested equity may actually decrease risk taking as executives keep

their shares and attempt to protect their wealth.

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Variable Description

Expected effect on

short term risk

level

Short term

salary_tc salary as a percentage of total annualcompensation -

bonus_tc bonus as a percentage of total annual

compensation +

salary_bonus_tccash compensation as a percentage of

total annual compensation +/-

bonus_interactiveinteraction term combining effects of

bonuses and salary +/-

Long term, current

shr_flow_tcvalue of shares granted in current year as

a percentage of total annual compensation -

opt_flow_tc value of options granted in current year asa percentage of total annual compensation

-

Long term, cumulative

vested_shr_tcvalue of vested shares as a percentage of

total annual compensation -

unvested_shr_tcvalue of unvested shares as a percentage

of total annual compensation +

vested_opt_tcvalue of vested options as a percentage of

total annual compensation -

unvested_op_tcvalue of unvested options as a percentage

of total annual compensation +

pct_shr_own percentage of total outstanding shares of

the firm owned by the CEO, excludingoptions -

total_shr_valuetotal value of all shares owned, excluding

options, as a percentage of total annual

compensation -

Control variables

age age of the executive +tenure number of years as CEO +

ceo_change1 if the firm has a new CEO during the

year, 0 otherwise +ln_assets natural log of total firm assets +/-

tobin_qTobin's Q, a measure of market power as

represented by market value vs. bookvalue of assets +/-

Fig. 1. Variable descriptions and expected relations to bank risk.

4.3. Dependent variables: SEER bank risk determinants

We first select dependent variables used in off-site bank surveillance. These variables are takenfrom Y9-C reports and have been proven to be effective determinants of the probability that a bank

will fail within two years (Cole & Gunther, 1995). These risk measures appear in the Federal Reserve’s

“System to Estimate Examination Ratings” (SEER) early warning model used for off-site surveillance

(Gilbert, Meyer, & Vaughan, 2000). We scale these variables by total assets, and group according

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Table 1

Summary descriptions of independent variables.

Variable N Mean Standard

deviation

25th percentile Median 75th percentile Max

Executive compensation

Salary tc 2006 84 0.33603 0.22825 0.14622 0.29640 0.47128 0.95869

Bonus tc 2006 84 0.07999 0.14810 0.00000 0.00000 0.10770 0.62578

Bonus interactive 2006 84 0.04343 0.09360 0.00000 0.00000 0.05047 0.49335

Shr flow tc 2006 84 0.17779 0.22959 0.00000 0.09584 0.26507 1.01875

Opt flow tc 2006 84 0.19165 0.22041 0.03060 0.12307 0.29171 1.25191

Vested shr tc 2006 83 13.57934 25.70625 1.87406 4.29479 11.15017 145.43938

Unvested shr tc 2006 84 0.53595 1.11297 0.00000 0.07704 0.67526 7.17922

Vested opt tc 2006 84 2.18078 3.36141 0.20549 1.34888 2.69428 24.87382

Unvested opt tc 2006 84 0.25089 0.34754 0.00000 0.10840 0.36895 1.57585

Control variables

Age 2006 85 57.22353 5.97291 53.00000 58.00000 61.00000 76.00000

Tenure 2006 85 9.34118 7.68820 4.00000 7.00000 14.00000 44.00000

CEO change 2006 85 0.09412 0.29373 0.00000 0.00000 0.00000 1.00000

ln assets 2006 85 16.74325 1.59345 15.63374 16.26343 17.73116 21.42297Tobin q 2006 85 1.12465 0.06264 1.08233 1.11890 1.16456 1.33710

Executive compensation data are from Compustat ExecuComp. All compensation variables are normalized by dividing by total

compensation (TDC1), defined as salary, bonus, all other, total value of restricted stock grants, total value of option grants,

and long term incentive payouts in 2006. Bonus interactive is the product of salary and bonus divided by total compensation.

Shr flowand opt floware thesharesand options values, respectively, awarded during theyear. Vested/unvestedshares/options

are the fair valuesof cumulative past awards of sharesand options, eithervested or unvested, as of 2006. Option portfolio values

are computed using the modified Black–Scholes–Merton methodology, as per ExecuComp. CEO change is a binary variable

taking the value of 1 if the firm has a new CEO during the fiscal year and 0 otherwise. ln assets is the natural log of firm assets.

Tobin q is Tobin’s Q, a measure of market power wherein market valuation is compared to book value; a number greater than

one indicates the market value of the firm is greater than the replacement cost of its assets.

to their predicted impact on bank risk. The first group represents predicted increases in risk, andincludes:

• DelqLoan30d are a bank’s interest-accruing loans which are between 30 and 89 days past due;• DelqLoan90+d are a bank’s interest-accruing loans which are at least 90 or more days past due;• NonAccruLoan refers to the bank’s delinquent loans which are not accruing interest;• ForclRealEst is the book value of foreclosed real estate;• JumboCDs is the value of domestic certificates of deposit, $100,000 or greater in value.

The remaining SEER-based variables are expected to have a negative relation to risk. These variables

include:

• TangibleCapital is the bank’s equity, less goodwill;• OpIncome is netoperating income before extraordinary items,less thegain (loss)on sale of securities;• LoanLossResrv is the allowance for loan and lease loss reserves;• InvSecurities is the book value of investment securities;

We also use a market-based measure of bank default risk called the expected default frequency

(EDF), calculated as in Crosbie and Bohn (2003). A bank’s distance to default is calculated as the dif-

ference between the market value of assets and the book value of debt, divided by the volatility of the

bank’s assets. We map the distance measure into a default probability by assuming a normal distribu-

tion. EDF increases with asset volatility and decreases with the difference between the market value

of assets and the book value of debt.Additionally, we include dependent variables that should be larger for banks that were heavily

involved in the risky activities leading up to the financial crisis. We separate the crisis-centric risk

variables fromthe SEERrisk framework variables to avoid contaminatingour measures and “predicting

the last crisis.” These variables have not traditionally been measures of bank risk but were proven,

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ex post , to be relevant risk measures. Several of these reporting items were not mandated by the

Fed until recently, while new crisis-sensitive variables such as ‘synthetic and other collateralized

debt obligations’, ‘retained beneficial interests in securitizations’, and ‘loans pending securitization’

attracted reporting mandates in 2008.

• OtherMBS : Other mortgage backed securities are often called ‘private label’ MBS because they are

often comprised of securitized sub-prime mortgages; these securities are not guaranteed by govern-

ment backed agencies. For this investigation OtherMBS are securities comprised of first and second

liens on one to four family residential properties.• %SecuritizInc is net securitization income as a percentage of the bank’s net income. Non-interest

income could diversify bank income streams and decrease risk; alternatively, it been shown to

increase bank risk (Stiroh, 2004). We consider securitization income risky in context, due to the

prevalence of subprime mortgage securitization.• Trading Assets are assets held at fair value with the intention to sell quickly. These include OtherMBS

and other securities such as credit default swaps. We include this as a measure of non-traditional

banking activity as compared to typical bank assets, loan portfolios.• Recourse includes financial standby letters of credit, performance standby letters of credit, recourse

and direct credit substitutes, and other financial assets sold with recourse. Recourse exposes banks

to the risk that securities already sold by the bank will underperform and be ‘put back’ to the bank.

We exclude commercial letters of credit, securities lent, or risk participations in bankers acceptances

in order to focus on what was most likely to be shared across the sample during the crisis: recourse

on MBS-type securities.

Table 2 reports summary statistics of risk variables. By the end of 2008, the mean EDF was greater

than 25%. At the 75th quartile the default probability rises to almost 50%. Other mortgage-backed

Table 2

Summary statistics of dependent variables.

Variable N Mean Standard deviation 25th percentile Median 75th percentile Max

Bank risk measures

DelqLoan30d 36 0.01043 0.00685 0.00647 0.00995 0.01334 0.03155

DelqLoan90d 36 0.00404 0.00516 0.00098 0.00221 0.00420 0.02418

NonAccruLoan 36 0.01262 0.00943 0.00564 0.01013 0.02212 0.03396

ForclRealEst 36 0.00176 0.00166 0.00059 0.00143 0.00249 0.00701

TangibleCapital 36 0.07446 0.01671 0.06273 0.07644 0.08475 0.10310

OpIncome 36 0.00080 0.01829 -0.00905 0.00487 0.01368 0.02500

LoanLossResrv 36 0.01226 0.00565 0.00981 0.01172 0.01481 0.02737

InvSecurities 36 0.17962 0.09282 0.11669 0.14863 0.22280 0.44337

JumboCDs 36 0.08355 0.03873 0.06234 0.07480 0.10957 0.16700

EDF 35 0.25288 0.29844 0.00224 0.17171 0.49277 0.96225Bank risk behaviors

OtherMBS 45 0.00086 0.00311 0.00000 0.00000 0.00003 0.01850

Trading Assets 85 0.01212 0.04001 0.00000 0.00000 0.00473 0.27061

%SecuritzInc 85 0.02083 0.08133 0.00000 0.00000 0.00000 0.58251

Recourse 85 0.03797 0.03872 0.01332 0.02431 0.04713 0.19950

Bank risk measure variables are scaled by total value of bank assets as of fiscal year 2008. Bank risk behavior variables are scaled

by the total value of bank assets as of fiscal year 2006 with the exception of %SecuritizInc which is scaled by net income in 2006.

DelqLoan30d andDelqLoan90dare thevalues of delinquent bank loans with a past-dueperiod of 30–89 or90+ days, respectively,

but still accrue interest and are therefore ‘performing’. NonAccruLoan is the value of loans that are no longer accruing interest.

ForclRealEst is the book value of foreclosed real estate. TangibleCapital is bank equity less goodwill. OpIncome is net income

less extraordinary items and gains (losses) on the sale of securities. LoanLossReserv is the value of reserves against losses

in loans and leases. InvSecurities is the value of investment securities. JumboCDs is the value of all domestic certificates of

deposit greater than $100,000. EDF is expected default frequency. OtherMBS is the value of ‘other’ or private label mortgagebacked securities not guaranteed by government backed agencies. Trading Assets is the value of all marketable securities held

for trading purposes, including mortgage backed securities and credit default swaps. %SecuritzInc is the percentage of income

resultingfrom securitization activity. Recourse is thevalueof guarantees made by thebank to thebuyers of securitized products,

and includes financial standby letters of credit, performance standby letters, recourse and direct credit substitutes, and other

assets sold with recourse.

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securities comprise a small percentage of total assets, even at the height of their popularity and asset

valuations. Almost all banks retained some recourse on their books, but at the 75th percentile is

less than 5% of the asset value. Securitization income shows that only a few banks actively pursued

securitization income in addition to traditional banking activities. That said, those that did securitize

did so aggressively. At the 75th percentile securitization income is negligible but quickly jumps to a

maximum of 58% of net income.

5. Methodology

We run two sets of regressions, the first assessing a bank’s risk using commonly known bank risk

factors, while the second set exploits the clarity of hindsight to link executive pay to specific bank

activities that contributed to the financial crisis. All regressions lag compensation variables by two

years to address the endogeneity between contemporaneous compensation and bank risk. The two

year lag structure allows enough time for compensation policies to affect the risks we investigate.

One- and three-year lags were rejected for parsimony, as they yield no substantial improvements in

model fitness. Our basic model follows:

Risk Measuret = ˛+ ˇ

1[Compensation Variablest −2] + ˇ

2[Control Variablest ] + εt

We control for the firm-specific characteristics of size and market power with the natural log of

total assets and Tobin’s Q. Larger, more powerful firms are more likely to diversified in their income

streams and therefore more likely to weather financial crises. Conversely, if firms are large enough to

pose systemic risk, they might take on more risk if there is an implicit assumption that the government

will not allow systemically important firms to collapse. We control for a change in the CEO during the

year, as well as the age and tenure of the CEO to measure the effects of experience and distance

to retirement. CEOs that are newer to their post and those who are relatively young, and therefore

presumed to be further from retirement, may be more likely to decrease short-term risk and focus on

long-term incentives. Conversely, elder CEOs would likely experience an increased short-term focusas they approach retirement, as their options and stock grants are largely vested and their wealth

is decreasingly tied to the success of the bank. Thus, we predict that bank risk increases with CEO

tenure and age. Overconfidence and hubris arguments also predict a positive relationship between

tenure, age, and risk. We expect both of these factors to compress CEO planning horizons and promote

short-term risk-taking activity.

The first set of regressions tests the relationship between bank risk variables used in offsite

monitoring programs and CEO compensation incentives. Our second series of regressions uses CEO

compensation variables from 2004 to explain crisis-related bank activities in 2006. We use trad-

ing assets, OMBS, recourse, and securitization income from 2006, the “good times” when revenues

produced from these risky activities were at their highest levels.

Both sets of tests use cross-sectional OLS regressions, with Breush–Pagan/Cook–Weisberg tests

to check for the presence of heteroskedasticity. When heteroskedasticity is present, we rerun the

regressions with standard errors robust to heteroskedasticity. This is often the case with the crisis-

centric risk variables of recourse, trading assets, other mortgage backed securities, and securitization

income. In most cases the results are unaffected, and when the difference is significant we report the

robust results.

6. Results

The first set of regressions focus on the Federal Reserve’s System to Estimate Examination Rat-

ings (SEER) bank risk variables. Regressions are expanded to broaden the scope of the investigation

each round such that short term, then long term, then all compensation variables are included in theregressions on bank risk.

Table 3 reports results of regressions of short-term cash incentives, salary and bonuses, on SEER

risk variables. Total cash compensation is not a statistically significant predictor of risk, though it

approaches statistical significance with regard to decreased tangible capital.

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Table 4 repeats the previous regression but includes a variable measuring the percentage of out-

standing shares owned by the CEO in order to capture the effects of long-term cumulative equity

compensation on bank risk. Interestingly, short-term cash compensation becomes negative and sig-

nificant with regard to tangible capital with the addition of CEO ownership, which is also negative and

highly significant to tangible capital at the 1% level. Also, firms with high CEO ownership levels also

show higher, marginally significant levels of investment securities relative to all assets. A 1% increase

in CEO ownership decreases tangible capital by 0.88% and increases the percentage of investment

securities to total assets by 3.54%.

Table 5 reports regression results of cash compensation and the dollar value of shares owned by

the CEO regressed on SEER bank risk variables. Cash compensation loses significance with regard to

decreases in tangible capital but maintains the negative relationship. Higher CEO equity value retains

the negative and statistically significant relationship to tangible capital and also shows a marginally

significant relationship to increased expected default frequency.

The compensation variables in our investigations are consistently overshadowed by the narrative

generated by our control variables. We controlled for the age and tenure of the CEO, whether there

was a change in the firm CEO that year, and for the size and market power of the firm. CEO age and

tenure are positivelyand consistentlysignificant with regard to non-accruingand delinquent loans andnegatively significant with regard to operating income. These findings provide evidence that the older

the CEO and the longer he or she has been at the firm, presumably then the closer to retirement and

the more risky the bank. This provides some evidence of a short-term orientation on the part of older,

tenured bank executives. We also find that the size of the firm is positively and significantly correlated

with increased expected default frequency at the 5% level. This suggests that larger firms are more

likely to default, providing evidence supporting the argument that insured deposits and, perhaps, the

assumption on the part of bank executives that the largest firms are too big to fail, encourage moral

hazard and the exploitation of the government safety net. However, market power as represented by

Tobin’s Q is negatively and significantly correlated to bank risk as represented by delinquent and non-

accruing loans and expected frequency of default and positively correlated with operating income, all

at the 1% level.Table 6 broadens the investigation of CEO compensation and SEER risk variables by breaking com-

pensationinto its myriad components. Expecteddefaultfrequency (EDF) is a measureof the probability

of default within the next two years. It is therefore a short term risk metric whereas increases in EDF

point to an increase in short-term risk.

High salaries relative to total compensation, as expected, increase operating income and signifi-

cantly decrease EDF at the 5% level. High bonuses, by themselves, are also shown to decrease EDF.

However, high salaries in the presence of high bonuses, as represented by the interaction term, are

positively and significantly correlated with expected default frequency at the 5% level. High bonuses,

when coupled with high salaries, show a marked turn to short term risk taking; a 1% increase in this

interaction term increases EDF by 3.37%, even though high salaries and high bonuses, independent of

one another, show decreases in short term risk taking. A 1% increase in salary (bonus) as a percent-age of total compensation decreases EDF by 0.46% (2.10%). Thus it is not bonuses per se that are the

problem, but the combination of high salary and bonuses that may be cause for concern.

Both share grants and vested shares arepositively correlated with short term bank risk at the10 and

5% levels, respectively, supporting the findings of Fahlenbrach and Stulz (2009) that CEO incentives

are properly aligned with shareholders. A 1% increase in share grants or vested shares increases EDF

by 0.43% and 0.01%, respectively. Options, both vested and unvested, are marginally but negatively

correlated with short term risk, supporting the argument that option compensation properly provides

long term incentives to managers.

Table 7 reports results from the second vein of our investigation, where we relate compensation to

the banking activities proven ex post to be contributors to the financial crisis. Compensation variables

from2004are regressed on other mortgagebacked securities, trading assets, netsecuritizationincome,and recourse variables in 2006 to capture any relationship between compensation and crisis-specific

activity prior to the collapse of the real estate market, thus, at the height of these activities. We find

no significant relationship between bonuses and risk, though the interaction between high bonuses

and high salaries is a marginally significant predictor of higher trading assets relative to total bank

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Table 7

Short and long term compensation components and crisis-specific bank risk behaviors.

OtherMBS 2006 Trading Assets 2006 Net sec income 2006 Recourse 2006

Salary tc 2004 0.00776 0.02937 0.01364 0.04799

(0.22) (0.48) (0.89) (0.28)

Bonus tc 2004 0.00024 −0.15885 −0.29831 0.04258

(0.99) (0.12) (0.24) (0.69)

Bonus interactive 2004 0.00632 0.33058** 0.52337 0.02492

(0.68) (0.02) (0.12) (0.86)

Shr flow tc 2004 0.00931 0.03671 −0.01138 0.02614

(0.13) (0.41) (0.92) (0.58)

Opt flow tc 2004 0.00926 0.02728 0.09744 0.02962

(0.15) (0.50) (0.34) (0.49)

Vested shr tc 2004 0.00001 −0.00002 0.00131***−0.00005

(0.80) (0.89) (0.00) (0.76)

Unvested shr tc 2004 0.00052 0.00353 0.00248 −0.00560

(0.38) (0.37) (0.80) (0.19)

Vested opt tc 2004 −0.00004 0.00014 −0.00876** 0.00087

(0.83) (0.92) (0.02) (0.56)Unvested opt tc 2004 0.00011 0.00012 0.00066 −0.00209

(0.80) (0.96) (0.91) (0.40)

Age 2004 −0.00005 −0.00067 −0.00585** 0.00068

(0.73) (0.55) (0.04) (0.56)

Tenure 2004 0.00006 0.00005 0.00041 −0.00103

(0.49) (0.95) (0.82) (0.19)

CEO change 2004 0.00909*** 0.02433 0.02235 −0.03704

(0.00) (0.27) (0.68) (0.12)

ln assets 2004 0.00032 0.00967**−0.00239 0.01410***

(0.57) (0.04) (0.84) (0.01)

tobin q 2004 −0.00898 −0.15527*−0.38456* 0.03816

(0.43) (0.08) (0.08) (0.68)

R2 0.541 0.601 0.411 0.383

N 38 61 61 61

The dependent variables are bank risk behaviors just before the crisis and presumably at relative high points, in 2006. The

independent variables are CEO compensation separated into their components in 2004 together with the vector of control

variables. OtherMBS is the value of ‘other’ or private label mortgage backed securities not guaranteed by government backed

agencies. Trading Assets is the value of all marketable securities held for trading purposes including mortgage backed securities

and credit default swaps. %SecuritzIncis thepercentage of incomeresulting from securitization activity. Recourse is thevalue of

guarantees made by the bank to the buyers of securitized products and includes financial standby letters of credit, performance

standby letters, recourse and direct credit substitutes, and other assets sold with recourse. Executive compensation data are

from Compustat ExecuComp. All compensation variables are normalized by dividing by total compensation (TDC1), defined as

salary, bonus, all other, total value of restricted stock grants, total value of option grants, and long term incentive payouts in

2004. Bonus interactive is the product of salary and bonus divided by total compensation. Shr flow and opt flow are the shares

and options values, respectively, awarded duringthe year. Vested/unvested shares/optionsare the fair values of cumulativepast

awards of shares and options, either vested or unvested, as of 2006. Option portfolio values are computed using the modified

Black–Scholes–Merton methodology as per ExecuComp. CEO change is a binary variable taking the value of 1 if the firm has anew CEO during the fiscal year and 0 otherwise. ln assets is the natural log of firm assets. Tobin q is Tobin’s Q, a measure of

market power wherein market valuation is compared to book value; a number greater than one indicates the market value of

the firm is greater than the replacement cost of its assets.

Numbers in parentheses are p-values. Values in bold are statistically significant, with the significance level indicated with

asterisks.* Statistical significance at the 10% level.

** Statistical significance at the 5% level.*** Statistical significance at the 1% level.

assets. Vested shares are positively and significantly correlated with securitization income at the 1%

level, though vested options are negatively correlated with securitization income at the 5% level. Notsurprisingly, larger firms were more likely to have higher levels of trading assets and to hold recourse

on their books at the 5 and 1% levels, respectively. Once again, however, firms with more market

power were marginally less likely to have higher percentages of trading assets and securitization

income.

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Murphy, K. J. (2000). Performance standards in incentive contracts. Journal of Accounting and Economics, 30(3), 245–278.Obama, B. (2010, January). Remarks by the President on financial reform. Office of the Press Secretary.Palia, D. (2000). The impact of regulation on CEO labor markets. Rand Journal of Economics, 31(1), 165–179.Stiroh, K. J. (2004). Diversification in Banking: Is Noninterest Income the Answer? Journal of Money, Credit and Banking , 36(5),

853–882.Thompson, J. B., & Yan, Y. (1997). FDICIA and bank CEO compensation: An empirical investigation. Working Paper Series.

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