non-executive incentives & bank risk-taking

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Non-Executive Incentives & Bank Risk-Taking Viral Acharya (NYU Stern, NBER & CEPR) Lubomir P. Litov (Univ. of Arizona & WFC, Univ. of Pennsylvania) Simone M. Sepe (Toulouse School of Economics & Univ. of Arizona) May 18 th 2013 American Law & Economics Association Meeting, Vanderbilt University

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May 18 th 2013. Non-Executive Incentives & Bank Risk-Taking. Viral Acharya (NYU Stern, NBER & CEPR) Lubomir P. Litov (Univ. of Arizona & WFC, Univ. of Pennsylvania) Simone M. Sepe (Toulouse School of Economics & Univ. of Arizona). - PowerPoint PPT Presentation

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Page 1: Non-Executive Incentives &  Bank Risk-Taking

Non-Executive Incentives &

Bank Risk-Taking

Viral Acharya (NYU Stern, NBER & CEPR)

Lubomir P. Litov (Univ. of Arizona & WFC, Univ. of Pennsylvania)

Simone M. Sepe (Toulouse School of Economics & Univ. of Arizona)

May 18th 2013

American Law & Economics Association Meeting, Vanderbilt University

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Research Questions

• What are the effects (if any) of bank non-executive (i.e., middle-level managers’, henceforth NE) compensation policies on bank holding companies (BHC) risk-taking & on BHC value?

• What are the determinants of such policies? In particular, to what extent does the market influence these incentives?

• Are there any normative implications?

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Motivation

• In this paper, we re-examine the paradigm in law & finance literature whereas:

• Executives determine NE incentives (e.g., Bebchuk & Fried, 2010).

• Hence, bank risk-taking in response to NE incentives is an executive incentive alignment problem.

• At least anecdotally (e.g., Rajan (2010)) NE incentives are important for bank risk taking & bank value.

• Moreover, there is role for competition in determining NE incentives.

• High-powered incentives to non-executives may lead to losing them to competitors.

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Motivation

“As long as the music is playing, you’ve got to get up & dance.”

“We’re still dancing.”

(Charles Prince)

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Two Empirical Hypotheses

• NE compensation policies in BHC before the crisis were only sensitive to increase revenue which resulted in excessive risk taking and, ultimately, lower bank value.

• The distorted risk incentives underlying BHCs’ NE compensation policies were the product of a negative externality engendered by bank competition for NE services.

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Executive Compensation

• Mixed evidence of the impact of CEO incentives on bank risk choices:

• Bebchuk & Spamann (2010) and Cheng, Hong, & Sheinkman (2010).

• Fahlenbrach & Stulz (2011).

Non-Executive Compensation

Overall literature scope is limited due to lack of cross-sectional data.

• Experimental Data

• Cole,Kanz & Klapper (2012) and Agarwal & Ben-David (2012).

• Single Lender Data

• Berg, Puri, & Rocholl (2012); Hertzberg, Liberti, & Paravisini (2011); and Gee & Tzioumis (2012).

Bank Risk Taking

Factors to influence bank risk-taking include • Deposit Insurance & Competition → Keeley (1990) among many others.• Ownership & Bank Regulation → Laeven and Levine (2009).• Bank Size → Demsetz and Strahan (1997).• Bank Franchise Value → Demsetz, Saidenberg, & Strahan (1997).• Monetary Policy → Landier, Sraer and Thesmar (2011).• Creditor Rights → Houston et al. (2010).• Risk Management Governance Mechanisms → Ellul and Yerramilli (2012).

.

Prior Literature

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During the financial crisis of 2007-2009:

1. Pre-crisis Cash & Bonus NE compensation incentives had a significant positive effect on bank risk taking.

2. Pre-crisis Stock NE compensation incentives had a significant negative effect on bank risk taking.

3. Pre-crisis NE compensation incentives affected bank risk-taking primarily trough the part of these incentives specific to peer-group performance.

4. Effects (1) and (3) above were stronger for banks w/ higher pre-crisis employee turnover & were weaker for banks w/ high pre-crisis excess NE compensation.

5. Pre-crisis NE total compensation incentives to above-peer group performance were more important in determining bank risk taking.

6. Pre-crisis NE Cash & Bonus compensation incentives lowered bank value, while NE Stock compensation incentives increased bank value.

Main Findings & Contributions

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1. We contribute to the bank risk taking literature by testing for a new (to the literature) factor to influence bank risk taking & bank value.

2. As such, we document an inefficiency in bank NE compensation policies, caused by competition among banks to hire NE.

3. Methodologically, we outline a novel cross-sectional proxy for non-executive incentives.

4. Lastly, we contribute to the literature on employee stock-ownership, showing that ESOP plans add value through curbing employee risk taking incentives.

Main Findings & Contributions

Page 9: Non-Executive Incentives &  Bank Risk-Taking

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Data

Collect Data from a Bank Regulatory Database.- Contains information on quarterly bank holding

company accounting data collected by the Federal Reserve Bank of Chicago.

Data available for 77 BHCs:- Only banks w/ available data.- Banks that survived the financial crisis.

 Other data:

- CRSP & Compustat (control variables). - ExecuComp (CEO incentives).- Option Metrics (Implied volatility).

Page 10: Non-Executive Incentives &  Bank Risk-Taking

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The Empirical Problem of Incentives

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The Empirical Problem of Incentives

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Non-Executive Compensation Elasticity

• Measures of Incentives (2002-2006):

• Elasticity of NE compensation: quarterly variation of total compensation (net of executive pay) w.r.t. quarterly variation of Total Interest Income (TII), or Net Interest Income (incl. Loan & Losses Provisions), Total Income, or Net Income.

• Maximal elasticity w.r.t. TII.

• I.e., banks may reward volume rather than quality of loan products.

𝐥𝐧 ( 𝑪𝒐𝒎𝒑𝒊𝒕

𝑪𝒐𝒎𝒑 𝒊𝒕−𝟏)=𝒂𝒊+𝒃𝒊𝟏 ,𝑻𝑰𝑰

𝑪𝒐𝒎𝒑× 𝒍𝒏( 𝑻𝑰𝑰 𝒊𝒕

𝑻𝑰𝑰 𝒊𝒕 −𝟏)+𝒃𝒊𝟐 ,𝑻𝑰𝑰

𝑪𝒐𝒎𝒑 ×𝒍𝒏( 𝑬𝑴𝑷 𝒊𝒕

𝑬𝑴𝑷 𝒊𝒕−𝟏)+𝒃𝒊𝟑 ,𝑻𝑰𝑰

𝑪𝒐𝒎𝒑× 𝒍𝒏( 𝑴𝑪𝑨𝑷 𝒊𝒕

𝑴𝑪𝑨𝑷 𝒊𝒕−𝟏)+𝜺 𝒊𝒕

Page 13: Non-Executive Incentives &  Bank Risk-Taking

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Key Independent Variables0

510

15

20

Density

.9 .95 1 1.05 1.1Salary_TII_Elasticity

0.5

11.5

2Density

-2 -1 0 1 2 3Stock_TII_Elasticity

05

10

15

Density

.9 .95 1 1.05 1.1TotalComp_TII_Elasticity

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Non-Executive Elasticity & Bank Risk-Taking

Measures of Risk (2007-2009): (1) Aggregate Risk; (2) Tail Risk; (3) Implied Volatility; (4) Z-Score.

Non-executive cash compensation incentives positively impact bank risk-taking.

In 2007-2009, the effect of NE cash compensation on risk is between 29.5% and 35.9%, instead effect of CEO compensation is, in some instances, 5.7%!

Non-executive stock compensation incentives negatively impact bank risk-taking, but stock incentives are only 2%!

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Cash & Stock Compensation Effects (Table 7)

Dep. Variable: Tail Risk

Independent Variables: (1) (2) (3) (4)

0.063*** 0.074***

t-stat (2.83) (3.71)

-0.001** -0.001***

t-stat (2.0) (3.80)

0.062**

t-stat (2.16)

CEO Delta (mean 2003-2006)   -0.001* -0.001* -0.001** -0.001*

t-stat   (1.92) (1.64) (2.03) (1.75)

CEO Vega (mean 2003-2006)   -0.011 -0.011 -0.009 -0.010

t-stat   (1.13) (1.17) (1.05) (1.10)

(control variables not shown for brevity)

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Cash & Stock Compensation Effects (Table 7) – Alternative Risk Measures

Dep. Variables: Aggregate Risk   Implied Volatility   Z-Score

Independent Variables: (1) (2) (3) (4)   (5) (6) (7) (8)   (9) (10) (11) (12)

0.149***    

0.182***  

1.148**    

1.041**  

-4.09***    

-3.955*

**

t-stat(4.91

)    (5.62

)  (2.49

)    (2.36

)  (3.44

)     (3.68)

 -

0.003  

-0.004

*     0.014   0.008    

-0.035

**   -0.012

t-stat  (1.57

)  (1.95

)    (1.01

)  (0.71

)    (2.28

)   (0.86)

   0.119

***         0.72***        

-3.38**

*  

t-stat    (3.75

)        (2.81

)        (3.57

)  CEO Delta (mean 2003-2006)  

0.0001 0.001

0.0001

0.0001   -0.005 -0.016 -0.006 -0.007  

0.054*

**

0.0666**

-0.008

0.0592***

t-stat   (0.73) (1.20) (0.49) (0.89)   (0.82) (1.21) (0.81) (0.80)   (2.72) (2.05) (0.20) (3.75)

CEO Vega (mean 2003-2006)  

-0.022

-0.023

-0.020

-0.022  

0.062*

* 0.054* 0.074*

0.061*

*  

-0.085*

**

-0.063*

**

-0.084

***

-0.0838

***

t-stat   (1.2) (1.22) (1.12) (1.15)   (1.99) (1.79) (1.91) (2.01)   (4.76) (3.67) (4.39) (4.82)(control variables not shown for brevity)

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Employee Turnover (Table 10A)

Panel A.   Tail RiskControl Variables (1) (2) (3) (4)

0.06**     0.07***

t-stat (2.23)     (3.03)

  -0.001   -0.001t-stat   (0.79)   (1.51)

    0.06**  t-stat     (2.29)  

  0.046***     0.18***

t-stat   (2.73)     (3.36)

    -0.008***   -0.011**

t-stat     (2.62)   (2.25)

      .039***  t-stat       (2.79)  

Employee Turnover (2003-2006)   -0.042 0.006* -0.03 -0.13t-stat   (0.68) (1.72) (0.54) (1.15)

(control variables not shown for brevity)

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Excess Cash Compensation (Table 10B)

Panel B.   Tail RiskControl Variables (1) (2) (3) (4)

.053**     .063***

t-stat (2.18)     (2.55)

  -.001**   -.001***

t-stat   (2.26)   (4.1)

    .051**  t-stat     (2.21)  

  -0.13*     -0.254*

t-stat   (1.93)     (1.67)

    0.004   -0.005t-stat     (1.02)   (0.62)

      -0.067*  t-stat       (1.74)  

Excess Cash Compensation (estimated 2003-2006)   0.001 -0.009*** -0.002 0.011

t-stat   (0.11) (3.91) (0.42) (0.55)(control variables not shown for brevity)

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Competition Effect

• To verify the relationship b/n competition for NE & their incentives, we consider:

- Sensitivity of NE compensation to BHC-specific performance & to peer-specific performance.

- Impact of turnover (as proxy for competition).

• NE compensation more sensitive to peer-specific performance.

• Turnover positively impacts bank risk-taking.

• Above-peer-group compensation (i.e., excess wage) negatively impacts bank risk-taking.

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Peer Effects Estimation

where peer-specific performance defined as:

and, where bank-specific performance, i.e., , is defined as the residual of a regression of on

,

ln ( 𝑇𝐼𝐼 𝑡

𝑇𝐼𝐼𝑡 −1)= 1

𝑁 ∑𝑖=1

𝑁 𝑇𝐼𝐼𝑖𝑡

𝑇𝐼𝐼 𝑖𝑡− 1

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Peer Group Choice

• Empirical challenge is to identify the peer group as it is possible that peer group performance is driven by a common latent factor.

• Potential solution: choose different reference group for different banks. Heterogeneity in peer group choice allows us to use performance of “peer’s peer” as valid instrument to capture peer group’s performance.

• Example. • Bank A1 has peer group, banks (A2, B1). • Bank B1 has a peer group, banks (B2, A1). • B2 performance relevant instrument for A1

performance because:1. Relevant to A1 performance (influences

performance of direct peer B1) &2. Exclusive to A1 performance (i.e., achieves

effect on A1 performance only through peer group).

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Market Short-Term Performance Effect (Table 8)

Dep. Variables:Tail Risk

AggregateRisk

Implied Volatility

Z-Score

Independent Variables: (1) (2) (3) (4) (5) (6) (7) (8)

0.0853**

0.0858**

0.136**

*

0.132**

*

0.955**

* 0.899** -4.05*** -4.01***

t-stat (2.58) (2.5) (6.31) (5.2) (2.68) (2.25) (8.45) (7.91)

0.0003  

-0.002**

*  

-0.044**

*   -0.054  

t-stat (0.27)   (3.19)   (5.32)   (1.41)  

CEO Delta (mean 2003-2006) -0.001 -0.001 -0.001 -0.001 0.014 0.010 -0.07*** -0.07***

t-stat (1.31) (1.3) (0.22) (0.32) (1.41) (1.05) (3.1) (3.11)

CEO Vega (mean 2003-2006) 0.0001 0.0001 -0.008 -0.007 0.006 0.043 0.238*** 0.265***

t-stat (0.03) (0.06) (0.59) (0.55) (0.16) (1.03) (2.91) (3.0)

(control variables not shown for brevity)

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Asymmetric Effects Estimation

We estimate

with denoting an indicator variable that is equal to one if

.

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Market Asymmetric Performance Effect (Table 9)

Dep. Variables:Tail Risk

Aggregate Risk

ImpliedVolatility

Z-Score

Independent Variables: (1) (2) (3) (4)

-0.0009 0.006* 0.043 0.081*

t-stat (0.11) (1.61) (1.42) (1.11)

0.078*** 0.131*** 0.45*** -1.023***

t-stat (2.75) (2.63) (9.12) (3.19)

CEO Delta (mean 2003-2006) -0.0009* -0.0001 -0.010 -0.063***

t-stat (1.77) (0.55) (1.05) (4.86)

CEO Vega (mean 2003-2006) -0.007 -0.013 0.07** 0.168***

t-stat (0.91) (0.79) (1.98) (4.28)

(control variables not shown for brevity)

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Bank Value (Table 11)

Dep. Variable: Tobin’s Q

Independent Variables: (1) (2) (3)

-0.2879***    

t-stat (3.89)    

    0.001  

t-stat   (0.65)  

    -0.2973***

t-stat     (3.78)

    0.00066

t-stat     (1.48)

CEO Delta (mean 2003-2006) -0.0113*** -0.0093** -0.0142***

t-stat (6.64) (2.43) (24.57)

CEO Vega (mean 2003-2006) 0.0166*** 0.017*** 0.0149**

t-stat (3.27) (3.36) (2.62)

(control variables not shown for brevity)

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Robustness

• Potential concern w/ empirical design is that both pre-crisis incentives & within-crisis risk exposure may reflect the level of BHC specialization in particular product lines (e.g. subprime loans).

• If such product specialization is not controlled for in our tests, or if it influences dependent and independent variables in these tests in a non-linear way, a correlated-omitted variable bias in our empirical results would arise.

• To address endogeneity concern we use a comprehensive sample that extends from 1994 through 2010 and we use an alternative approach based on a system GMM estimation (Blundell and Bond (1998)).

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GMM Analysis

Dep. Variable: Tail Risk

Control Variables (1) (2) (3) (4) 

0.61*** 0.68***

t-stat (6.30) (3.20)

-.008*** -0.012*

t-stat (3.20) (1.80)

0.41***

t-stat (3.56)

CEO Delta (t-1) -.009*** -.007*** -0.01*** -.008***

t-stat (3.10) (2.80) (3.30) (3.0)

CEO Vega (t-1) .019*** .015*** .018*** .017***

t-stat (4.20) (3.70) (4.0) (3.90)

(control variables not shown for brevity)

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GMM Analysis

Dep. Variable: Aggregate Risk

Control Variables (1) (2) (3) (4) 

0.47**     0.56**

t-stat (1.98)     (2.02)

  -0.011   -.014*

  (1.20)   (1.81)

t-stat     0.34*  

    (1.79)  

0.004 0.010 0.007 0.000

t-stat (0.45) (0.61) (0.53) (0.05)

CEO Delta (t-1) .007*** .007*** .006*** .006***

t-stat (3.80) (4.49) (3.60) (3.55)

CEO Vega (t-1) 0.47**     0.56**

t-stat (1.98)     (2.02)(control variables not shown for brevity)

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GMM Analysis

Dep. Variable: Implied Volatility

Control Variables (1) (2) (3) (4) 

2.50***     2.81***

t-stat (3.20)     (3.90)

  -.004**   -.02***

  (2.43)   (3.12)

t-stat     1.18***  

    (3.30)  

0.172* 0.150 0.177* 0.169*

t-stat (1.87) (1.65) (1.93) (1.86)

CEO Delta (t-1) -0.015 -.026* -0.017 -0.010

t-stat (1.40) (1.89) (1.59) (1.20)

CEO Vega (t-1) 2.50***     2.81***

t-stat (3.20)     (3.90)(control variables not shown for brevity)

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GMM Analysis

Dep. Variable: Z-Score

Control Variables (1) (2) (3) (4) 

-13.2***     -14.1***

t-stat (4.1)     (4.1)

  -0.13**   -0.04*

  (2.6)   (1.8)

t-stat     -10.8***  

    (4.9)  

0.19** 0.23* -0.040 0.19***

t-stat (2.6) (1.93) (0.3) (3.24)

CEO Delta (t-1) -0.3*** -.18*** -.28*** -.29***

t-stat (4.12) (3.56) (4.12) (4.59)

CEO Vega (t-1) -13.2***     -14.1***

t-stat (4.1)     (4.1)

(control variables not shown for brevity)

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Executive Compensation Reform?

• Improving executive compensation practices not enough to solve the problem of excessive bank risk-taking.

• NE risk incentives are independent from executive risk incentives.

• The root of the problem is the negative externality produced by bank competition for non-executives.

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Limiting Competition for Non-Executives

• Direct: Making employment contracts relational.

• Non-compete provisions for NEs: property rule.

• Pigouvian tax on mobility: liability rule.

• Clawback provisions contingent on mobility.

• Excess compensation (contracts are less subject to renegotiation).

• Pigouvian subsidy: Regressive tax (or tax deduction) on compensation based on tenure.

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Non-Executive Deferred Stock Compensation

• We find that stock compensation negatively impacts risk-taking, but is only 2% of total compensation.

• Back-loading stock compensation into future periods increases employer specificity.

• Rethink ownership between capital and labor providers when moral hazard is severe and cannot be fully controlled by contract.

• Implementation strategies:- Tough: Mandatory rules.- Soft: Tax deductions.

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Thank You.