Compensation gaps among top
executives: the role of the peer groups
Chi-Hung Chang
Min-Teh Yu
Jen-Chih Kuo
Graduate Institute of Finance
National Chiao Tung University
Abstract

This paper explores if the peer groups make a
difference in the explanation of the compensation gaps
between top executives.

We find that the productivity theory is applied to the
large firm peer and the high CEO compensation peer.

The tournament effect is applied for the small firm peer
and the pay gaps between non-CEO executives.
Background
 Determinants of CEO compensation
Personal characteristics – age, educational level, tenure, …
 Firm characteristics – firm performance
 Benchmarking pay level of peer groups (Bizjak et al. (2008, JFE);
Faulkender and Yang (2010, JFE))
 The relevance of benchmarking pay
 Representing reservation wage (Hokmstrom and Kaplan (2003, JACF))
 Self-serving (Bizjak et al. (2011, JFE); Faulkender and Yang (2010, JFE))
 How are peer groups determined?
 Industry and size – Bizjak et al. (2008, JFE)
 Actual disclosure – Faulkender and Yang (2010, JFE)

Background
Compensation of non-CEO executives
 Productivity – Higher level managers are more productive than lower
level ones.

Tournament – Compensation difference can motivate executives’
efforts.
 Which one dominates?
 Tournament incentives (Kale et al. (2009, JF))
 Productivity differential (Masulis and Zhang (2012, working))
 Research question:
 Is the peer group responsible for the difference between the
tournament and productivity effect?

Why is non-CEO executives’ pay relevant?
Team work of the corporation organization
 The gaps between CEO and other top executives vary materially
across companies (Masulis and Zhang (2012, working)).
Why?
 Is the CEO really extremely talented?
 Does the firm want to stimulate non-CEO executives’ efforts to
multiply the benefit of team work?
 Contagion effect in CEO compensation across companies
(Bereskin and Cicero (2012, JFE)). Non-CEO executives’ pay
in other companies would be referred when determining
their rewards.

Theories of compensation gaps

Productivity theory
Rosen (1981, 1982); Gabaix and Landier (2008) –
Multiplicative productivity models



Higher level managers
level ones.
are more productive than lower
Tournament theory
Lazear and Rosen (1981); Green and Stokey (1983);
Rosen (1986)


A mechanism to elicit executives’ efforts
Empirical evidence of compensation gaps





Productivity differentials
Finkelstein and Hambrick (1988, SMJ); Gibbs (1995,
JAE); Prendergast (1999, JEL); Anabtawi (2005, ELJ);
Masulis and Zhang (2012, working)
Tournament effect
Main et al. (1993, JLE); Eriksson (1999, JLE); Bognanno
(2001, JLE)
Controversy still remains.
Hypotheses



H1: The compensation gap in the larger peer is more likely to
reflect productivity differentials.
H2: The compensation gaps in the peer group with higher CEO
pay would more likely support the productivity theory.
H3: The compensation gaps between executives below the
CEO would more probably reflect the tournament theory.
Empirical strategy




Data: Compensation data from Execcucomp over 19932005; firm characteristics data from Compustat.
Determining peers based on industry
(following Bizjak et al., 2008, JFE).
Industry: 2-digit SIC code
Size: median sales



Size peer groups
CEO compensation peers
Executives compensation peers
and
size
Variables

CEO compensation gap

Total gap = log(total CEO compensation/median total compensation of nonCEO executives)
Short-term and long-term gap are defined similarly.

Non-CEO executives compensation gap


Total gap = log(Highest non-CEO total compensation/lowest non-CEO
executives’ total compensation)
Short-term and long-term gap are defined similarly.

Tournament measure: number of non-CEO executives

Productivity measure: executive’s position tenure, the
average pay growth over the past three years

Variables (Cont.)

Control variables

Incentive variables





CEO pay growth
CEO tenure
CEO alignment
Executives alignment
Firm characteristics variables
 Lagged assets
 Lagged market-to-book ratio
 R&D intensity
Descriptive statistics
Industry-size above the peer median
Industry-size below the peer median
Diff.
CEO_Total
6673.24
(9188)
2906.11
(4967)
3767.12***
CEO_ST
1793.26
(9188)
841.50
(4967)
951.76***
CEO_LT
4879.98
(5287)
2064.61
(4374)
2815.37***
Executives_Total
2376.06
(37418)
1040.55
(19653)
1335.51***
Executives_ST
792.85
(37418)
377.32
(19653)
415.53***
Executives_LT
1583.21
(22396)
663.23
(17645)
919.98***
Compensation level
Notes: Figures in parenthesis are observations. *** Significant at the 1% level.

Executives pay is substantially higher in larger firms.
Descriptive statistics (Cont.)
Industry-size above the peer median
Industry-size below the peer median
Diff.
Compensation gap (dollar term, in thousand)
Total gap
4594.06
(9188)
1995.24
(4967)
2598.82***
Short term gap
1056.24
(9188)
489.57
(4967)
566.67***
Long term gap
3551.69
(9188)
1151.50
(4967)
2040.19***
Total gap
3.31
(9188)
3.08
(4967)
0.24***
Short term gap
2.52
(9187)
2.32
(4967)
0.19***
Long term gap
4.67
(9188)
4.49
(4967)
0.18
Compensation gap (ratio)
Notes: Figures in parenthesis are observations. *** Significant at the 1% level.

Compensation gaps between CEO and other executives are substantial.
Regression results on size peers
Total Gap
Size above peer
Size below peer
group median
group median
VP_Num
CEO_Alignment
VP_Alignment
CEO_Tenure
Lag_Assets
Lag_MTB
R&D_Intensity
Constant
Observations
Year dummies and industry
fixed effects
R-squared
Adj R_squ

Short-term Gap
Size above peer
Size below peer
group median
group median
Long-term Gap
Size above peer
Size below peer
group median
group median
0.023*
(0.013)
0.000
(0.002)
-0.038*
(0.019)
0.007
(0.011)
0.020***
(0.006)
0.001
(0.006)
-0.025*
(0.014)
0.808***
(0.103)
0.044***
(0.016)
0.007***
(0.002)
-0.068***
(0.010)
-0.039***
(0.014)
0.065***
(0.012)
0.010**
(0.004)
0.019
(0.021)
0.376***
(0.109)
-0.007
(0.013)
-0.006**
(0.003)
-0.024
(0.015)
0.073***
(0.013)
-0.012
(0.009)
-0.031**
(0.013)
-0.088***
(0.022)
1.051***
(0.121)
0.008
(0.015)
0.005***
(0.002)
-0.062***
(0.011)
0.062***
(0.015)
0.024*
(0.013)
-0.004
(0.003)
-0.039
(0.024)
0.632***
(0.132)
0.035**
(0.017)
-0.000
(0.003)
-0.049*
(0.026)
-0.024*
(0.014)
0.010
(0.008)
-0.013**
(0.006)
-0.035*
(0.019)
1.109***
(0.142)
0.051**
(0.024)
0.005*
(0.003)
-0.086***
(0.013)
-0.074***
(0.021)
0.045**
(0.018)
0.001
(0.005)
0.074**
(0.031)
0.518***
(0.165)
6,498
Yes
3,654
Yes
6,488
Yes
3,641
Yes
6,498
Yes
3,654
Yes
0.053
0.0422
0.105
0.0874
0.051
0.0404
0.139
0.122
0.046
0.0350
0.079
0.0605
Tournament effect is more significant and the magnitude is larger for
the small size peer.
Regression results on size peers (Cont.)
Total Gap
Size above peer group Size below peer group
median
median
VP_Pay_Growth
Vp_Tenure
CEO_pay_Growth
CEO_Alignment
VP_Alignment
CEO_Tenure
Lag_Assets
Lag_MTB
R&D_Intensity
Constant
Observations
Year dummies and industry fixed
effects
R-squared
Adj R_squ

Short-term Gap
Size above peer
Size below peer
group median
group median
Long-term Gap
Size above peer
Size below peer
group median
group median
0.000
(0.000)
-0.137***
(0.026)
0.000***
(0.000)
-0.002
(0.002)
-0.018
(0.017)
0.108***
(0.015)
0.024***
(0.008)
0.001
(0.006)
-0.048**
(0.019)
1.014***
(0.114)
0.000
(0.000)
-0.056
(0.039)
0.000***
(0.000)
0.002
(0.003)
-0.068***
(0.010)
0.045
(0.028)
0.075***
(0.017)
0.009
(0.007)
0.006
(0.028)
0.543***
(0.141)
-0.000*
(0.000)
-0.064*
(0.038)
0.000
(0.000)
-0.008**
(0.003)
-0.006
(0.012)
0.128***
(0.021)
-0.021
(0.016)
-0.028
(0.020)
-0.140***
(0.041)
1.133***
(0.178)
0.000
(0.000)
-0.015
(0.030)
-0.000
(0.000)
0.005**
(0.002)
-0.057***
(0.008)
0.047**
(0.022)
0.056***
(0.011)
0.003
(0.004)
-0.025
(0.021)
0.444***
(0.080)
-0.000
(0.000)
-0.155***
(0.036)
0.000***
(0.000)
-0.003
(0.003)
-0.024
(0.023)
0.088***
(0.021)
0.015
(0.011)
-0.010
(0.007)
-0.059**
(0.027)
1.406***
(0.163)
0.000
(0.000)
-0.103*
(0.059)
0.000**
(0.000)
0.000
(0.004)
-0.085***
(0.014)
0.063
(0.041)
0.044*
(0.026)
-0.004
(0.010)
0.051
(0.043)
0.930***
(0.200)
3,454
Yes
1,654
Yes
3,452
Yes
1,653
Yes
3,454
Yes
1,654
Yes
0.092
0.0729
0.200
0.165
0.072
0.0525
0.290
0.260
0.072
0.0523
0.142
0.105
Productivity effect is significant for the large size peer.
Regression results on CEO compensation peers
Total Gap
CEO pay above peer
CEO pay below peer
group median
group median
VP_Num
CEO_Alignment
VP_Alignment
CEO_Tenure
Lag_Assets
Lag_MTB
R&D_Intensity
Constant
Observations
Year dummies and industry
fixed effects
R-squared
Adj R_squ

Short-term Gap
CEO pay above peer CEO pay below peer
group median
group median
Long-term Gap
CEO pay above peer
CEO pay below peer
group median
group median
0.024
(0.019)
0.007**
(0.003)
-0.044
(0.031)
0.046**
(0.019)
0.017**
(0.007)
-0.007
(0.006)
-0.015
(0.019)
0.827***
(0.151)
0.038***
(0.012)
0.002
(0.002)
-0.058***
(0.009)
-0.056***
(0.009)
0.043***
(0.006)
0.005
(0.005)
-0.016
(0.015)
0.582***
(0.079)
0.006
(0.022)
-0.002
(0.004)
-0.022
(0.023)
0.071**
(0.030)
-0.009
(0.012)
-0.022***
(0.008)
-0.094***
(0.035)
1.115***
(0.163)
0.001
(0.011)
-0.000
(0.001)
-0.050***
(0.009)
0.046***
(0.009)
0.018***
(0.006)
-0.015**
(0.007)
-0.068***
(0.017)
0.693***
(0.081)
0.038
(0.024)
0.008*
(0.004)
-0.062
(0.042)
0.052*
(0.026)
0.005
(0.010)
-0.016**
(0.007)
-0.005
(0.026)
1.010***
(0.206)
0.048***
(0.017)
0.000
(0.002)
-0.072***
(0.012)
-0.098***
(0.014)
0.030***
(0.008)
-0.008
(0.006)
-0.001
(0.021)
0.804***
(0.115)
3,431
Yes
6,721
Yes
3,428
Yes
6,701
Yes
3,431
Yes
6,721
Yes
0.087
0.0675
0.062
0.0515
0.054
0.0344
0.060
0.0498
0.082
0.0627
0.049
0.0385
Tournament proxy is significant for the low CEO pay peer.
Regression results on CEO compensation peers
(Cont.)
Total Gap
CEO pay above peer CEO pay below peer
group median
group median
VP_Pay_Growth
VP_Tenure
CEO_pay_Growth
CEO_Alignment
VP_Alignment
CEO_Tenure
Lag_Assets
Lag_MTB
R&D_Intensity
Constant
Observations
Year dummies and industry
fixed effects
R-squared
Adj R_squ

Short-term Gap
CEO pay above
CEO pay below peer
peer group median
group median
Long-term Gap
CEO pay above peer CEO pay below peer
group median
group median
-0.000
(0.000)
-0.094**
(0.041)
0.000
(0.000)
0.008*
(0.004)
-0.024
(0.025)
0.128***
(0.030)
0.018**
(0.009)
-0.012*
(0.007)
-0.052**
(0.026)
1.160***
(0.201)
0.000
(0.000)
-0.136***
(0.025)
0.000***
(0.000)
-0.003
(0.002)
-0.051***
(0.010)
0.057***
(0.015)
0.049***
(0.007)
0.004
(0.008)
-0.031
(0.021)
0.932***
(0.096)
-0.000***
(0.000)
0.016
(0.053)
0.000
(0.000)
-0.005
(0.007)
-0.001
(0.014)
0.108*
(0.057)
-0.025
(0.019)
-0.028
(0.019)
-0.157**
(0.062)
1.292***
(0.240)
-0.000
(0.000)
-0.094***
(0.029)
-0.000
(0.000)
-0.002
(0.002)
-0.045***
(0.009)
0.095***
(0.013)
0.020**
(0.008)
-0.011**
(0.006)
-0.087***
(0.026)
0.683***
(0.074)
-0.000
(0.000)
-0.143***
(0.055)
0.000
(0.000)
0.007
(0.005)
-0.033
(0.034)
0.172***
(0.044)
0.005
(0.012)
-0.025***
(0.009)
-0.057
(0.036)
1.445***
(0.303)
0.000
(0.000)
-0.151***
(0.037)
0.000***
(0.000)
-0.005
(0.003)
-0.065***
(0.015)
0.030
(0.022)
0.039***
(0.011)
-0.018*
(0.011)
-0.025
(0.030)
1.388***
(0.137)
1,989
Yes
3,119
Yes
1,988
Yes
3,117
Yes
1,989
Yes
3,119
Yes
0.094
0.0610
0.116
0.0955
0.070
0.0364
0.103
0.0825
0.092
0.0592
0.088
0.0674
Productivity proxy is significant for the high and low CEO pay peers.
Regression results on non-CEO executives
compensation peers
Total Gap
VP pay above peer
VP pay below peer
group median
group median
VP_Num
CEO_Alignment
VP_Alignment
CEO_Tenure
Lag_Assets
Lag_MTB
R&D_Intensity
Constant
Observations
Year dummies and industry
fixed effects
R-squared
Adj R_squ

Short-term Gap
VP pay above peer
VP pay below peer
group median
group median
Long-term Gap
VP pay above peer
VP pay below peer
group median
group median
0.216***
(0.018)
0.076***
(0.017)
-0.032
(0.025)
-0.003
(0.015)
0.014**
(0.006)
0.007**
(0.004)
0.025
(0.019)
-0.344**
(0.136)
0.209***
(0.012)
0.040***
(0.007)
-0.014
(0.014)
-0.077***
(0.010)
0.026***
(0.006)
0.020***
(0.004)
0.030**
(0.015)
-0.361***
(0.085)
0.116***
(0.016)
0.054***
(0.013)
-0.015
(0.021)
-0.012
(0.013)
0.017***
(0.005)
0.001
(0.002)
0.016
(0.015)
0.001
(0.117)
0.098***
(0.012)
0.022***
(0.006)
-0.009
(0.009)
-0.008
(0.008)
0.008
(0.005)
0.001
(0.009)
-0.003
(0.012)
0.116
(0.075)
0.274***
(0.026)
0.065***
(0.022)
0.009
(0.036)
-0.019
(0.023)
-0.004
(0.009)
-0.008
(0.005)
0.030
(0.029)
-0.173
(0.266)
0.301***
(0.019)
0.037***
(0.008)
0.004
(0.019)
-0.116***
(0.015)
-0.005
(0.009)
0.004
(0.006)
0.044*
(0.023)
-0.245*
(0.127)
3,792
Yes
6,375
Yes
3,790
Yes
6,359
Yes
3,792
Yes
6,375
Yes
0.163
0.148
0.142
0.132
0.170
0.154
0.087
0.0768
0.113
0.0960
0.110
0.0999
Tournament proxy is significant for the high and low non-CEO
executives pay peers.
Regression results on non-CEO executives
compensation peers (Cont.)
Total Gap
VP pay above peer
VP pay below peer
group median
group median
VP_Pay_Growth
VP_Tenure
CEO_pay_Growth
CEO_Alignment
VP_Alignment
CEO_Tenure
Lag_Assets
Lag_MTB
R&D_Intensity
Constant
Observations
Year dummies and industry fixed
effects
R-squared
Adj R_squ

Short-term Gap
VP pay above peer
VP pay below peer
group median
group median
Long-term Gap
VP pay above peer
VP pay below peer
group median
group median
-0.001*
(0.001)
0.029
(0.048)
0.001*
(0.001)
0.067***
(0.019)
-0.031
(0.029)
-0.063***
(0.024)
0.025**
(0.010)
0.009
(0.006)
-0.014
(0.029)
0.710***
(0.213)
0.000
(0.001)
-0.014
(0.031)
0.000
(0.001)
0.032***
(0.009)
-0.019
(0.014)
-0.073***
(0.022)
0.046***
(0.009)
-0.003
(0.011)
0.056**
(0.028)
0.412***
(0.112)
-0.000
(0.000)
0.014
(0.036)
0.000
(0.000)
0.048***
(0.016)
-0.022
(0.024)
-0.056***
(0.020)
0.008
(0.008)
0.003
(0.004)
0.015
(0.022)
0.389***
(0.090)
-0.001***
(0.000)
0.020
(0.024)
0.001***
(0.000)
0.021***
(0.006)
-0.009
(0.010)
-0.021
(0.017)
0.016**
(0.007)
-0.016**
(0.007)
0.028
(0.019)
0.433***
(0.103)
-0.001*
(0.001)
-0.010
(0.064)
0.001*
(0.001)
0.066***
(0.024)
-0.011
(0.039)
-0.077**
(0.033)
0.020
(0.013)
-0.004
(0.008)
-0.034
(0.040)
1.167***
(0.345)
0.000
(0.001)
-0.057
(0.045)
0.000
(0.001)
0.030***
(0.010)
-0.014
(0.015)
-0.105***
(0.033)
0.033**
(0.013)
-0.035**
(0.015)
0.043
(0.040)
0.878***
(0.164)
1,672
Yes
2,341
Yes
1,671
Yes
2,337
Yes
1,672
Yes
2,341
Yes
0.188
0.153
0.130
0.103
0.222
0.188
0.141
0.115
0.132
0.0942
0.101
0.0732
Productivity proxy is generally not significant for the high and low
non-CEO peers.
Conclusions

This paper examines the role of the peer group on the
tournament and productivity effect of the compensation gaps.

Major findings

Productivity differentials are observed in the large size peer and high CEO
compensation peer.

Tournament effect is observed in the small size peer and the pay gap among
non-CEO executives.

Our findings could help reconcile the debate on the
tournament and productivity effect of the compensation gaps
of top executives.
Thank You!