How Much Do CEO Incentives Matter?pages.stern.nyu.edu/.../research/HMDIM-Presentation.new.pdf ·...

How Much Do CEO Incentives Matter?

Robert Tumarkin

January 13, 2010

NYU, Stern School of Business


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Introduction

Research Questions

How can we quantify the impact of CEO incentives on firm perfor-mance?

1 / 25How Much Do CEO Incentives Matter?

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Introduction

Research Questions


Do CEO incentives substitute for otherwise poor corporategovernance?

How does the CEO herself influence the value of incentives?


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Introduction

Econometric Issues

What is the right framework?

Random-effects panel research finds a positive associationbetween CEO incentives and performance

Morck, Shleifer, and Vishny (1988), Zhou (2001)

Fixed-effects panel research finds no relationship between CEOincentives and performance

Himmelberg, Hubbard, and Palia (1999), Palia (2001)

First-difference panel research finds a positive association andsometimes a negative association between CEO incentives andfirm performance

Fahlenbrach and Stulz(2009a,b)


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Introduction

Econometric Issues

What are the identification challenges?

Fixed-effects and first-difference panels address only one type ofendogeneity, time-constant firm-manager effects

CEO characteristics may not be sufficiently strong instruments forCEO incentives

Palia (2001)


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Introduction

Econometric Issues

What are the identification challenges?

Fixed-effects and first-difference panels address only one type ofendogeneity, time-constant firm-manager effects

CEO characteristics may not be sufficiently strong instruments forCEO incentives

Palia (2001)

What are other challenges?

Firm performance can be a persistent processes

Strict exogeneity may be violated


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Introduction

This paper

Economically meaningful and intuitive results

Median incentives account for 3.7% of firm value (Tobin’s q)Incentives act especially strongly when corporate governance limitsthe CEO’s pecuniary riskIncentives create greater value when the CEO’s portfolio consists ofrestricted stock and unvested options

Econometric and empirical step forward

Fixed-effects with strong instruments for identificationRelaxing of strict exogeneity assumptionAllowance for dynamic firm performance


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Incentives, endogeneity, and identification

Outline

1 Incentives, endogeneity, and identification

2 Results

3 Maximizing the Effects of Incentives

4 Robustness Tests

5 Conclusion


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A predictive panel regression

yi ,t+1 = αyi ,t + βBi ,t + ( ηi + φj ,t+1 + εi ,t+1 )

Firm performance

CEO incentives

Fixed effects for CEO-firm i

Time t + 1 industry mean

Time t + 1 innovation


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Incentives

Definition

Sensitivity of changes in the CEO’s existing security portfoliovalue to changes in the firm’s stock price.

What is the best way to express this sensitivity?

B =∆ $Wealth

∆ ln Equity Value· 1

$ Wage

Edmans, Gabaix, and Landier (2009)


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Incentives

Definition

Sensitivity of the value of the CEO’s existing stocks and optionsas a percent of annual salary for a percent change in stock price.

What is the best way to express this sensitivity?

B =∆ $Wealth

∆ ln Equity Value· 1

$ Wage

Edmans, Gabaix, and Landier (2009)


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A predictive panel regression

yi ,t+1 = αyi ,t + βBi ,t + ( ηi + φj ,t+1 + εi ,t+1 )

Main Problems

Endogeneity - e.g. managers are rewarded for “lucky” performance

Dynamics - e.g. Microsoft remains solvent despite the launch ofVista

Feedback - e.g. Pfizer goes on acquisition binge after the accidentaldiscover of Viagra


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3 step empirical approach

1 First differencing

Removes CEO-firm fixed effectsEstimation equation in terms of changes in incentives

2 Instrument construction

Changes in incentives instrumented by returns of peers and laggedCEO portfolio information

3 Estimation technique

Two-step efficient GMM allows for feedback and dynamics


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Step 1: First differencing

∆yi ,t+1 = α∆yi ,t + β∆Bi ,t + ∆φj ,t+1 + ∆εi ,t+1

Removes CEO-firm fixed effects ηi

Still need to identify ∆Bi ,t


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Step 2: Instrumentation of ∆B

Changes in incentives due to stock price movements are given by

Bt−1 · rt−1,t

(1 +

γBS ,t−1

∆BS ,t−1St−1

)

But, these are not exogenous

Bt−1 and rt−1,t are correlated with εt

rt−1,t may anticipate εt+1


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Identification assumptions

1 Twice lagged incentive levels are independent of currentperformance innovations

2 After controlling for time-varying industry performance mean, afirm’s performance innovation is independent of its peers’ stockreturns

Similar to Hausman (1997)


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Instrument for ∆Bt

Zt−1,t = Bt−1 · rt−1,t

(1 +

γt−1

∆t−1· St−1

)

Let r−it−1,t be the equally weighted average of these company

returns, excluding firm i , computed with monthly rebalancing


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Zt−1,t = Bt−2 · rt−1,t

(1 +

γt−2

∆t−2· St−1

)




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Zt−1,t = Bt−2 · r−it−1,t

(1 +

γt−2

∆t−2· St−1

)




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3 step empirical approach

1 First differencing

Removes CEO-firm fixed effectsEstimation equation in terms of changes in incentives

2 Instrument construction

Changes in incentives instrumented by returns of peers and laggedCEO portfolio information

3 Estimation technique

Two-step efficient GMM allows for feedback and dynamics


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Results

Outline


2 Results


4 Robustness Tests

5 Conclusion


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Results

Sample descriptive statistics

Variable Mean Sd P25 P50 P75

CEO Information:Annual Compensation ($million) 2.22 0.92 1.56 2.01 2.67Incentive Exposure (B) 21.9 28.4 4.5 10.3 24.5Age (years) 55.7 7.2 51.0 56.0 61.0Tenure (years) 8.1 6.9 3.0 6.0 11.0

Firm Size and Age:Aggregate Value ($billion) 3.3 4.6 0.7 1.5 3.6Book Leverage 0.22 0.18 0.05 0.20 0.34Firm Age (years) 21.8 14.6 10.0 17.0 33.0Sales ($billion) 2.0 3.0 0.4 0.9 2.1

Firm Performance:Tobin’s q 2.00 1.18 1.22 1.59 2.30Operating Income-to-Capital 0.9 1.2 0.3 0.6 1.2


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Results

Incentives and firm performance

Predicted Variable Tobin’s q Operating Income

Incentives B (x1000) 6.96** 4.15**(2.32) (2.12)

Log Sales ($million) -1.75*** -0.53***Acquisition Intensity -0.70 0.91Capital Expenditure Intensity -0.72 -0.68R and D Intensity 8.29*** -7.24***Book Leverage -0.25 -0.27Operating Margin -0.41 1.16**Tangible Capital -0.57*** -0.12Sales Growth 1 yr. 0.19 -0.10Lag Operating Income 0.43***

Observations 8119 6737Dummies Year Year

z-statistics (Windmeijer robust) in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1


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Results

Economic level of incentives

Incentive Level Median Mean

Tobin’s qValue 0.073 0.176Percent of Sample Mean (%) 3.7 8.8Percent of Sample Std. Dev. (%) 6.2 14.9

Operating Income-to-CapitalValue 0.04 0.10Percent of Sample Mean (%) 4.8 11.7Percent of Sample Std. Dev. (%) 3.6 8.7


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Maximizing the Effects of Incentives

Outline


2 Results


4 Robustness Tests

5 Conclusion


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Research Questions


Do CEO incentives substitute for otherwise poor corporategovernance?

How does the CEO herself influence the value of incentives?


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Corporate governance

Hypothesis:Incentives should be most effective when corporate governancelowers the CEO’s financial risk.

Index DescriptionProtection Director/officer protectionDelay Tactics to delay hostile biddersOther Takeover defensesState State levelVoting Shareholder rights

Higher index value ≡ Lower quality governance

Gompers, Ishii, and Metrick (2003)


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Corporate governance and Tobin’s q

Governance Index Protection Delay Voting Other State

B (x1000) 1.98 5.62* 2.89 9.89*** 6.01**(0.85) (1.73) (0.61) (2.59) (2.35)

B · Governance (x1000) 10.20** -2.52 1.51 -7.44 -6.34*(2.52) (-0.90) (0.28) (-1.41) (-1.96)

Governance 0.47 0.13 0.25 0.28 0.57(1.21) (0.44) (0.53) (0.68) (0.84)

Log Sales ($million) -1.44*** -1.58*** -1.58*** -1.35*** -1.63***Acquisition Intensity 0.53 -0.88 -0.93 -0.76 -0.80Capex Intensity -1.24** -0.15 -0.56 -0.23 -0.34R and D Intensity 4.50** 5.15** 7.76*** 3.08* 6.97***Book Leverage -0.31 -0.06 0.23 0.10 0.09Operating Margin -0.06 -0.16 -0.09 0.17 0.38Tangible Capital -0.25 -0.39** -0.43** -0.23 -0.46**Sales Growth 1 yr. 0.10 0.28 0.21 0.15 0.19

Observations 5673 6370 6708 4493 6395Dummies Year Year Year Year Year



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CEO discretion

Hypothesis:Incentives should be effective only as long as the CEO holdscompany stock or options.

Definition

Discretion Ratio =BNon−restricted Stock + BVested Options

BTotal


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CEO discretion

Predicted Variable Tobin’s q Operating Income

B (x1000) 13.50** -1.61(2.37) (-0.51)

B ·Discretion Ratiot−1 (x1000) -10.10* 6.92**(-1.74) (2.02)

Discretion Ratiot−1 0.102 -0.195Log Sales ($million) -1.86*** -0.50***Acquisition Intensity -1.14 1.01Capital Expenditure Intensity -0.43 -0.76R and D Intensity 8.32*** -6.32***Book Leverage -0.02 -0.32Operating Margin -0.37 1.10**Tangible Capital -0.54*** -0.09Sales Growth 1 yr. 0.30 -0.08Lag Operating Income 0.48***

Observations 6033 6737Dummies Year Yearz-statistics (Windmeijer robust) in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1


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Robustness Tests

Outline


2 Results


4 Robustness Tests

5 Conclusion


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Robustness Tests

Robustness

Results are robust to

1 Alternate industry definitions: 8, 19, and 64 time-varying industrymeans

2 Use of excess return instruments based on Fama & French 3-FactorRegressions

3 Exclusion of firm founders


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Robustness Tests

Alternate industry definitions

Number of industriesTobin’s q 8 19 64

B (x1000) 5.60* 4.17 5.35*(1.81) (1.38) (1.73)

Log Sales ($million) -2.03*** -2.02*** -1.90***Acquisition Intensity 0.83 0.72 -0.61Capex Intensity -1.70** -1.43** -0.60R and D Intensity 3.69 3.67 4.63*Book Leverage 0.13 0.08 -0.12Operating Margin -0.12 -0.21 0.05Tangible Capital -0.42** -0.40** -0.26Sales Growth 1 yr. 0.28 0.34 0.50**

Observations 8119 8119 8119Dummies Yr×8 Yr×19 Yr×64



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Conclusion

Outline


2 Results


4 Robustness Tests

5 Conclusion


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Conclusion

Conclusion

CEO incentives create significant economic value. Median incentivesare responsible for 3.7% of firm value (Tobin’s q).

CEO incentives substitute for poor corporate governancemechanisms limiting the CEO’s downside financial risk.

The structure of the CEO’s portfolio greatly influences the economicimpact of incentives.


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Robert Tumarkin

January 13, 2010

NYU, Stern School of Business

Thank you


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