Presentation by Michael-Paul James on Performance Peer Groups in CEO Compensation Contracts by Tor-Erik Bakke, Hamed Mahmudi, and Ashley Newton

1. Performance Peer Groups in
CEO Compensation Contracts
Tor-Erik Bakke, Hamed Mahmudi, and Ashley Newton
Presentation by Michael-Paul James

2. TABLE OF CONTENTS
All content in this presentation is quoted or paraphrased directly from paper.
01
Introduction
The questions, the setup,
the sources, the theories.
02
Empirical Analysis
Exploring the data
03
Enhanced Disclosure
Effects of SEC rule
change
04
Conclusions
The take-away
2

3. Introduction
The questions, the setup, the
sources, the theories.
01

4. 17%
2006
Increase of Relative Performance Evaluation (RPE)
in Chief Executive Officer (CEO)
pay packages
34%
2012
4
01

5. Of Total Executive Compensation
in Firms with RPE pay structures
32%
2012
5
01

6. Why RPE
● Relative Performance Evaluation (RPE) benefits
○ CEO performance can be more accurately
determined through the comparison of peer
company performances.
○ Tying CEO pay to relative performance minimizes
free rides and more fairly incentivizes.
6
01

7. Research Question
● How do firms choose performance peer groups
used in chief executive officer (CEO) relative
performance evaluation (RPE) contracts? (997)
7
01

8. Results Summary
● On average, firms disproportionately choose
underperforming peers.
● Firms generally select similar peers in size, leverage,
industry, index membership, operation structure,
historical performance correlation, and geographic
presence.
● Stock indexes are preferred to custom peer groups if
firm complexity makes peers difficult to discover or if
board members are busy and not independent.
● Compulsory legislation had no observable effect.
● 8
01

9. Theory
● Optimal Contracting Theory
● Managerial Power Theory
9
01

10. Optimal Contracting Theory & RPE
● Optimal Contracting Theory (OCT): Agents Balance
contracting, monitoring, and misbehavior (3 types
of agency costs) to minimize the total cost.
● Assumption:
○ Compensation contracts should utilize the most accurate
metrics of CEO performance.
○ Firms should select peers facing same risks and benefits.
● RPE removes noise to more accurately assess CEO
performance.
10
01

11. Managerial Power Theory & RPE
● Managerial power theory (MPT): Executive pay
often does not correlate with executive
performance; Executives receive meaningfully more
that economically efficient pay structures suggest.
● Assumption:
○ Powerful CEOs, who control boards, may strong arm members to
choose underperforming peers for RPE contracts.
● CEOs manipulate compensation through strategic
peer selection in RPE contracts
11
01

12. Data Sources
● SEC Form DEF 14A, Definitive Proxy Statement, 1998-2012
○ DEF 14A: Definitive Proxy Statement- Outlines details of voting options.
○ Contractual details of the CEO’s RPE contracts
● Incentive Lab RPE Contract Data, 1998-2012
○ Named Executive Officers (NEO) of the 750 largest, actively traded firms
in the USA.
● Supplemental Data
○ Data from Center for Research in Security Prices (CRSP)
■ Stock price performance of granting firms and peers
○ Data from Compustat
■ Financial characteristics
○ Data from Execucomp
■ CEO characteristics
○ Data from Institutional Broker’s Estimate System (I/B/E/S)
12
01

13. Table
1:
Panel
A
Choice
of
the
type
of
the
performance
peer
group:
Logistic
regressions
Panel A. Prevalence of relative performance evaluation with chosen peers disclosed by type of peer
Descriptive Statistics by Incentive Lab
All Custom peer groups Stock indices as peers
Percent of Percent of
total yearly total yearly
Year N N observations N observations
1998 77 27 35.06% 52 67.53%
1999 82 28 34.15% 56 68.29%
2000 82 25 30.49% 59 71.95%
2001 80 20 25.00% 60 75.00%
2002 81 24 29.63% 58 71.60%
2003 82 25 30.49% 57 69.51%
2004 98 40 40.82% 61 62.24%
2005 116 41 35.34% 77 66.38%
2006 184 112 60.87% 83 45.11%
2007 219 146 66.67% 86 39.27%
2008 231 151 65.37% 91 39.39%
2009 236 156 66.10% 90 38.14%
2010 268 181 67.54% 101 37.69%
2011 296 198 66.89% 113 38.18%
2012 344 219 63.66% 144 41.86%
Total Firm-year Obs. 2,476 1,393 1,188 13
01

14. Table
1:
Panel
B
&
C
Choice
of
the
type
of
the
performance
peer
group:
Logistic
regressions
Panel B. Types of metrics used as benchmarks for custom peer group RPE grants
Descriptive Statistics by Incentive Lab
1998–2012 1998–2005 2006–2012
Percent of Percent of Percent of
total total total
Metric N observations N observations N observations
TSRTotal Shareholder Return
998 71.64% 158 68.70% 840 72.23%
Accounting 586 42.07% 124 53.91% 462 39.72%
Firm-year-metric
observations 1,584 282 1,302
Panel C. Metrics used per firm-year for custom peer groups users benchmarking to TSR or accounting metrics
TSR (At Least 1) Accounting (Only)
Metric 1998–2012 1998–2005 2006–2012 1998–2012 1998–2005 2006–2012
Mean 1.44 1.68 1.39 1.60 1.69 1.58
Median 1.00 1.00 1.00 1.00 1.00 1.00
14
01

15. Empirical Analysis
Exploring the data
02

16. Peer Selection Process
● How do firms choose their performance peer group? (1003)
○ Human resources drafts pay recommendations.
○ Compensation Committee reviews and revises pay
recommendations.
■ Compensation consultant recommends terms and peer
selection when necessary.
○ Board of directors votes to approve compensation committee’s
pay recommendations
● Managers can influence any part of the process.
16
02

17. Index or Custom Peer Group
● What determines the choice between a custom peer group and a
stock index as the type of performance peer group for an RPE
granting firm? (1004)
○ Custom Peer Groups
■ Advantage: Custom peer groups more efficiently removes
exogenous events, unrelated to CEO performance.
■ Disadvantage: Customization is difficult to properly design
and susceptible to managerial manipulation.
○ Stock Index
■ Appropriate for complex multifaceted firms with unclear
peers, experiencing rapid growth, or board without time to
design custom peer groups.
○ Method: Logistic regression with choice of stock indices or
Custom Peer Group as dependent variable. 17
02

18. Table 2 & 6: Variable Definitions
● Log(total assets)
○ The logarithm of total assets.
● Multi-segment
○ An indicator variable set to 1 if a company has more than one business segment and 0 otherwise.
● Q(Ind)
○ The asset-weighted average Tobin’s Q ratio of the firm’s Fama–French 48 (Fama & French, 1997) industry
group where Tobin’s Q = (total liabilities + fiscal-year closing stock price × total shares
outstanding)/total assets.
● Inside CEO(Ind)
○ Proportion of internally hired CEOs of the firm’s Fama–French 48 (Fama & French, 1997) industry group.
● Industry analyst forecasts
○ Average number of analyst forecasts of firm’s Fama–French 48 (Fama & French, 1997) industry group.
● Log(firm age)
○ The number of years the granting company has been in business.
● Log(CEO tenure)
○ The number of years the present CEO has held the title of CEO.
● Log(board size)
○ The number of directors serving on the company’s board.
18
02

19. Table
2
(1)
Choice
of
the
type
of
the
performance
peer
group:
Logistic
regressions
Table 2. Choice of the type of the performance peer group: Logistic regressions
Exclusively stock
index
Exclusively custom peer
group
Index peer is a market
index, among index users
Variable (1) (2) (3) (4) (5) (6)
Log(total assets) 0.1627* 0.1615* -0.1773** -0.1708** -0.2857* -0.1745
(.068) (.070) (.042) (.050) (.075) (.262)
Multi-segment 0.2540 0.2557 -0.2680* -0.2729* 0.7214** 0.6854**
(.133) (.131) (.099) (.093) (.026) (.033)
Q(Ind) 0.0964 -0.5361 -2.1794***
(.812) (.162) (.001)
Inside CEO(Ind) -0.4696 -0.7045 8.3519***
(.767) (.648) (.004)
Industry analyst forecasts -0.4779 -0.4694 1.1947** 1.1173** -0.7224 -0.2180
(.381) (.387) (.018) (.026) (.395) (.793)
Log(firm age) -0.0001 -0.0049 -0.0496 -0.0298 0.1179 0.1811
(.999) (.975) (.744) (.844) (.660) (.486)
Log(CEO tenure) 0.1519 0.1501 -0.1484 -0.1427 -0.2713 -0.2378
(.391) (.397) (.378) (.395) (.402) (.459)
Log(board size) 0.3452 0.3402 0.1682 0.0984 1.5890* 1.2843
(.515) (.522) (.736) (.843) (.082) (.164) 19
01

20. Table 2 & 6: Variable Definitions
● CEO-Chairman duality
○ An indicator variable equal to 1 when the CEO is also Chairman of its board of directors and 0
otherwise.
● Compensation consultant
○ An indicator variable equal to 1 when a granting firm employs a compensation consultant and 0
otherwise.
● Number of busy board members
○ The number of directors serving on three or more outside boards.
● Independent directors
○ The proportion of directors that is independent.
● Co-opted boards
○ The fraction of the directors on the board that were appointed after the current CEO took office
(Source: Lalitha Naveen’s Website).
● S&P 500
○ An indicator variable set to 1 if a company belongs to the S&P 500 Composite Index and 0
otherwise.
20
02

21. Table
2
(2)
Choice
of
the
type
of
the
performance
peer
group:
Logistic
regressions
Table 2. Choice of the type of the performance peer group: Logistic regressions
Exclusively stock
index
Exclusively custom peer
group
Index peer is a market
index, among index users
Variable (1) (2) (3) (4) (5) (6)
CEO-Chairman duality 0.0405 0.0443 -0.0407 -0.0339 -0.3001 -0.4040
(.824) (.808) (.814) (.845) (.362) (.216)
Compensation consultant 0.6693*** 0.6695*** -0.2264 -0.2202 -0.9049* -0.7978*
(.010) (.010) (.355) (.369) (.050) (.086)
Number of busy board members 0.1437** 0.1414** -0.1152* -0.1145* -0.1432 -0.1215
(.035) (.039) (.076) (.078) (.232) (.306)
Independent directors -1.6826 -1.6943* 1.4402 1.4618 1.8693 2.2213
(.102) (.099) (.146) (.139) (.301) (.216)
Co-opted boards 0.2543 0.2610 -0.0140 -0.0375 1.2568* 0.8548
(.519) (.507) (.970) (.920) (.078) (.219)
S&P 500 -0.0432 -0.0410 0.0684 0.0498 0.2582 0.2755
(.844) (.852) (.745) (.812) (.527) (.499)
Industry fixed effects Yes Yes Yes Yes Yes Yes
Year fixed effects Yes Yes Yes Yes Yes Yes
N 870 870 870 870 355 355
Pseudo R2 .136 .136 .107 .105 .286 .281
01

22. Choosing Custom Peers
● Do factors supported by managerial power theory also contribute to
predicting the choice of performance peer firms? (998)
● How do custom peer group users choose their performance peers?
(1006)
● We employ a multivariate logit model:
○ Dependent variable, P (yijt
= 1), is set to 1 if peer j is member of performance
peer group of firm i in year t, 0 if otherwise.
22
P (yijt
= 1) = G (𝛼0
+ 𝛼1
Peer performancejt−1
+ 𝛼2
Peer correlationijt−1
+ 𝛼3
Match on industryijt−1
+ 𝛼4
Match on assetsijt−1
+ 𝛼5
Match on leverageijt−1
+ 𝛼6
Match on S&P 500ijt−1
+ 𝛼7
Number of peersit
+ 𝛼8
Match on business segmentsijt−1
+ 𝛼9
Match on geographic segmentsijt−1
+ 𝜀ijt
) 02

23. Table 3, 4, 5 & 7: Variable Definitions
● Peer performance
○ For peer firm j, the difference between the annualized total shareholder return (TSR) of the peer firm
and the mean annualized TSR of its TNIC (Text-based Network Industry Classifications) three-digit
industry group (Hoberg & Phillips, 2010, 2016) where the industry mean excludes the return of peer firm
j and where returns are computed as a function of monthly holding period returns.
● Peer correlation
○ Historical correlation of the peer and RPE granting firms’ stock return performance computed over the
12 months preceding the RPE grant date.
● Match on industry
○ An indicator variable set to 1 if the RPE granting and candidate peer firms match in terms of TNIC
three-digit industry affiliation (Hoberg & Phillips, 2010, 2016) and 0 otherwise.
○ Similar results for:
■ SIC (Standard Industrial Classification), 2 or 4 digits ■ FF-48 (Farma French 48)
■ NAICS (North American Industry Classification System), 4 digit
■ GICS (Global Industry Classification Standard), 4 or 8 digits.
■ NAICS (North American Industry Classification System), 6 digit- Different result but insignificant.
● Match on assets
○ An indicator variable set to 1 if the RPE granting firm’s total assets is within 50–200% of the candidate
peer’s total assets and 0 otherwise.
23
02

24. Table 3, 4, 5 & 7: Variable Definitions
● Match on leverage
○ An indicator variable set to 1 if the RPE granting firm’s Book Leverage Ratio is within 75–150% of
the candidate peer’s Book Leverage Ratio and 0 otherwise.
● Match on S&P 500
○ An indicator variable set to 1 if the RPE granting and candidate peer firms match on the criterion
of S&P 500 membership and 0 otherwise.
● Match on business segments
○ An indicator variable set to 1 if the RPE granting and candidate peer firms have the same number
of business segments and each of those segments matches on the same four-digit SIC industry
and 0 otherwise.
● Match on geographic segments
○ An indicator variable set to 1 if the RPE granting and candidate peer firms are both multinational
companies, defined as a company that reports foreign sales and/or has at least one international
segment, and 0 otherwise.
● Number of peers
○ The number of peer firms in the RPE granting firm’s disclosed custom peer group.
24
02

25. Table
3
Choice
of
performance
peers:
Logistic
regressions
performance
Dependent variable: Whether a candidate peer is chosen as a performance peer by an RPE granting firm
2006-2012 1998-2005
(1) (2) (3) (4) (5) (6)
Peer performancet-1
-.159*** -.151*** -.084
(.000) (.000) (.213)
Peer performancet
-.196*** -.191*** -.131*
(.000) (.000) (.080)
Peer correlation 2.406*** 2.653*** 2.414*** 2.661*** 2.138*** 2.135***
(.000) (.000) (.000) (.000) (.000) (.000)
Match on industry 3.721*** 4.276*** 3.720*** 4.275*** 4.541*** 4.547***
(.000) (.000) (.000) (.000) (.000) (.000)
Match on assets 1.380*** 1.457*** 1.379*** 1.455*** 1.235*** 1.233***
(.000) (.000) (.000) (.000) (.000) (.000)
Match on leverage 0.711*** 0.798*** 0.712*** 0.799*** 0.803*** 0.805***
(.000) (.000) (.000) (.000) (.000) (.000)
Match on S&P 500 0.124 0.240* 0.124 0.240* -0.861*** -0.865***
(.259) (.062) (.259) (.062) (.000) (.000)
Match on business segments 0.925*** 1.205*** 0.924*** 1.203*** 0.743** 0.737**
(.000) (.000) (.000) (.000) (.034) (.036)
Match on geographic segments 0.835*** 0.628*** 0.835*** 0.629*** 0.050 0.049
(.000) (.000) (.000) (.000) (.712) (.720)
Number of peers 0.022*** 0.021*** 0.022*** 0.021*** 0.000 0.000
(.000) (.000) (.000) (.000) (.925) (.924)
Firm fixed effects No Yes No Yes Yes Yes
Year fixed effects Yes Yes Yes Yes Yes Yes
Clustered standard errors Firm & Peer Firm & Peer Firm & Peer Firm & Peer Firm & Peer Firm & Peer
N 2,183,432 2,183,432 2,183,432 2,183,432 355,969 355,969
Pseudo R2
.373 .407 .373 .407 .411 .412
25

26. Choosing Custom Peers
● Confirmation of optimal contract theory predictions
● On average, Firms choose peers who match on
○ Historical Performance Correlations (12 month)
○ Industry ○ Size (Assets)
○ Leverage ○ Index Membership (S&P)
○ Operational Structure (Business Segments)
○ Geographical Presence
● On average, Firms choose peers who are underperforming in total
shareholder return (TSR) in their industry group (TNIC)
● Interesting note:
○ On average, Firms choose peers who perform poorly after peer
membership is determined, possibly due to informational
advantages of managers.
26
02

27. Active Rotation of Peers
● Are firms actively changing their custom peer groups or is it merely
the case that weak firms already included in peer groups in 2006
have persistently underperformed during our 6-year sample period?
(1011)
○ Multivariate logit model
○ Dropped firm characteristics (on average)
■ The most signs are as expected- diverging piers are
dropped, but most are not statistically significant
○ Added firm characteristics (on average)
■ Contemporaneous underperforming peers are added.
■ Historical performance is not significant with an unexpected
sign.
○ Retained firm characteristics (on average)
■ Underperforming firms are retained. 27
02

28. Table
4
The
dynamics
of
performance
peer
selection
Panel A: Adds versus potential
adds (1 for adds; 0 for potential
adds)
Panel B: Drops versus retained
(1 for drops; 0 for retained)
Panel C: Retained versus
potential adds (1 for retained; 0
for potential adds)
(1) (2) (3) (4) (5) (6)
Peer performancet-1
.063 -.269 -.176***
(.518) (.186) (.000)
Peer performancet
-.260** .005 -.293***
(.012) (.969) (.000)
Peer correlation 1.611*** 1.611*** -0.128 -0.113 2.182*** 2.198***
(.000) (.000) (.694) (.730) (.000) (.000)
Match on industry 3.120*** 3.122*** -0.515** -0.516** 3.692*** 3.692***
(.000) (.000) (.024) (.024) (.000) (.000)
Match on assets 1.114*** 1.113*** -0.083 -0.090 1.169*** 1.168***
(.000) (.000) (.621) (.593) (.000) (.000)
Match on leverage 0.587*** 0.584*** -0.172 -0.173 0.777*** 0.777***
(.000) (.000) (.197) (.196) (.000) (.000)
Match on S&P 500 0.635*** 0.637*** -0.370** -0.362** 0.837*** 0.838***
(.005) (.005) (.030) (.033) (.000) (.000)
Match on business segments 1.120*** 1.121*** -0.052 -0.050 1.025*** 1.024***
(.000) (.000) (.826) (.831) (.000) (.000)
Match on geographic segments 0.750*** 0.753*** -0.552* -0.544* 0.783*** 0.786***
(.000) (.000) (.052) (.057) (.000) (.000)
Number of peers 0.017** 0.017** -0.005 -0.004 0.019*** 0.019***
(.026) (.026) (.658) (.663) (.000) (.000)
N 542,602 542,602 2,901 2,901 1,307,681 1,307,681
Pseudo R2 .202 .203 .030 .028 .365 .365
28
02

29. Active Rotation of Peers
● Firms actively decrease the overall performance of the peer group
through adding more underperforming peers rather than removing
strong peers from the group.
○ Peer groups increased from 13.6 (2006) to 16.6 (2012)
○ Managerial power theory (MPT) predicts this result.
29
02

30. Weak Choosing Weak
● Do underperforming RPE granting firms have a greater tendency to
select weaker performance peers? (1013)
○ Multivariate logit model
■ Interaction Variables of all variables with the corporate
governance proxies (Panels A to C) and performance (D)
■ Peer determinants from the last 2 tables were included in
the model but left out of the output for simplicity.
● Variable Definition
○ High blockholder competition
■ An indicator that is 1 if blockholder competition, defined as
–1 × the Herfindahl-Hirschman Index (HHI) of blockholder
concentration (BHCOMP as defined in Dou et al., 2018)
■ Blockholders: shareholders with ownership ≥ 5 percent 30
02

31. Table
5:
Panel
A
&
B
Choice
of
performance
peers:
Sample
splits—Governance
and
performance
Panel A. Peer selection conditional on the proportion of directors appointed after the CEO assumed office
Co-opted Co-opted p-Value: Co-opted Co-opted p-Value:
boards >33% Boards ≤33% (1) - (2) boards >33% Boards ≤33% (4) - (5)
(1) (2) (3) (4) (5) (6)
Peer performancet-1
-.2247*** -.1721*** (.389)
(.000) (.001)
Peer performancet
-.2998*** -.2181*** (.170)
(.000) (.000)
N 824,461 706,102 824,461 706,102
Pseudo R2 .337 .339 .338 .339
Panel B. Peer selection conditional on whether the CEO is also chairman of the board of directors
CEO CEO p-Value: CEO CEO p-Value:
duality = 1 duality = 0 (1) - (2) duality = 1 duality = 0 (5) - (6)
(1) (2) (3) (4) (5) (6)
Peer performancet-1
-.1958*** -.2077*** (.845)
(.000) (.000)
Peer performancet
-.2675*** -.2420*** (.689)
(.000) (.000)
N 1,106,188 534,501 1,106,188 534,501
Pseudo R2 .354 .311 .354 .312
31
02

32. Table
5:
Panel
C
&
D
Choice
of
performance
peers:
Sample
splits—Governance
and
performance
Panel C. Peer selection conditional on whether blockholder competition is high or low
High
blockholder
competition = 1
High
blockholder
competition = 0
p-Value:
(1) - (2)
High
blockholder
competition = 1
High
blockholder
competition = 0
p-Value:
(4) - (5)
(1) (2) (3) (4) (5) (6)
Peer performancet-1
-.0097 -.2176*** (.025)
(.865) (.004)
Peer performancet
-.2358*** -.3487*** (.240)
(.000) (.000)
N 305,542 300,582 305,542 300,582
Pseudo R2 .287 .281 .288 .282
Panel D. Peer selection conditional on RPE grant firm performance
Below Median
TSR = 1
Below Median
TSR = 0
p-Value:
(1) - (2)
Below Median
TSR = 1
Below Median
TSR = 0
p-Value:
(4) - (5)
(1) (2) (3) (4) (5) (6)
Peer performancet-1
-.3435*** .0131 (.000)
(.000) (.770)
Peer performancet
-.1495*** -.2342*** (.162)
(.003) (.000)
N 963,256 1,220,176 963,256 1,220,176
Pseudo R2 .378 .369 .377 .370
32
02

33. Weak Choosing Weak
● Do underperforming RPE granting firms have a greater tendency to
select weaker performance peers? (1013)
○ Firms with Co-opted boards >33% choose more poorly
performing firms
○ Firms with CEOs as Chariman of the board choose marginally
better performing firms who contemporaneously perform worse
on average.
○ Firms with lower Herfindahl index numbers than industry mean
choose worse performing firms on average (low shareholder
power)
○ Firms with lower than average TSR choose firms with lower than
average TSR.
33
02

34. Enhanced Disclosure
Exploring the data
03

35. Exogenous Event: SEC Rule
● January 27, 2006: SEC presented revisions to
compensation rules for public comment.
● August 29, 2006: the SEC ordered enhanced
executive compensation disclosure requirements
for annual reports, proxy statements, and
registration requirements.
● December 15, 2006: All firms required to comply for
all statements filed.
35
01

36. Quasi-Natural Experiment
● Difference-in-Difference Model
○ Control Group: Firms who already disclosed their CEO RPE
contracts before 2006.
○ Treatment Group: Firms who had not disclosed their CEO RPE
contracts before 2006
■ Firms generally agree on RPE peer selection before the fiscal year. Therefore,
the Treated 2006 selection reveals hidden preferences.
36
2006 2007
Treatment Group
No Foresight
Peer Disclosure
Treatment: Compulsory
Peer Disclosure
Control Group
History of Voluntary
Peer Disclosure
Compulsory
Peer Disclosure
01

37. SEC Timing
1/1/2005 1/1/2006 1/1/2007 1/1/2008
37
2006 Peers Chosen 2005 Proxy Filed
Control Firms: Peers Disclosed
Treated Firms: Peers Not Disclosed
2007 Peers Chosen 2006 Proxy Filed
Control Firms: Peers Disclosed
Treated Firms: Peers Disclosed*
*2006 Peers were chosen before
disclosure requirement was known
SEC proposes
Disclosure Rule
SEC adopts
Disclosure rule
Disclosure Rule
goes into effect
1/27/2006
8/29/2006
12/15/2006
01

38. New Rules Same Results
● Do enhanced disclosure requirements affect the tendency of firms to
select underperforming peers? (999)
● Did enhanced disclosure change how performance peers are selected?
(1015)
○ We employ a difference-in-difference (DID) model (Panel B):
■ Dependent variable, P (yijt
= 1), is the probability that peer j is member of
performance peer group of firm i in year t after 2006, 0 if otherwise.
■ G(𝛽x): Logit Function
■ Dt
: dummy variable (=1) if event is after 2006
■ Ti
: indicator variable if firm belongs to treatment group.
■ Rt−1,j
: Industry adjusted stock return of potential peer.
P(yijt
= 1) = G(𝛽0
+ 𝛽1
Ti
+ 𝛽2
dt
+ 𝛽3
Ti
dt
+ 𝛽4
Rt−1,j
+ 𝛽5
Tj
Rt−1,j
+ 𝛽6
dt
Rt−1,j
+ 𝛽7
Ti
dt
Rt−1,j
+ zijt
𝛿 +
𝜀ijt
)
RPE granting firms:36 treated and 17 control firms 38
02

39. Table
6:
Panel
A
Change
in
disclosure
regime:
difference-in-differences
analysis
Panel A. Comparison of treated and control firms in the pre-event period (2006)
Summary Statistics
Control group Treated group
Variable N Mean Median N Mean Median
Log(total assets) 17 9.663 9.304 36 9.093 8.754
Number of business segments 17 2 1 36 1.611 1
Q(Ind) 17 1.529 1.694 36 1.36 1.371
Inside CEO(Ind) 17 0.803 0.806 36 0.813 0.812
Firm age (years) 17 39.765 55 36 40.556 51.5
CEO tenure (years) 17 5.176 5 36 5.306 4.5
Log(board size) 17 2.391 2.398 36 2.345 2.303
CEO–Chairman duality 17 0.941 1 36 0.75 1
Compensation consultant 17 0.294 0 36 0.306 0
Number of busy board members 17 1.588 2 36 0.833** 0.000**
Independent directors 17 0.833 0.875 36 0.813 0.838
39
03

40. Table
6:
Panel
B
Change
in
disclosure
regime:
difference-in-differences
analysis
Panel B. Difference-in-differences regressions
Dependent variable: Whether a candidate peer is chosen as a performance peer by an RPE granting firm
(1) (2) (3) (4)
Treated .009 .275 .013 .278
(.964) (.108) (.953) (.110)
Postregulation .032 -.147 .022 -.152
(.426) (.336) (.630) (.304)
Treated × Postregulation -.032 .062 -.018 .076
(.528) (.727) (.738) (.674)
Peer Performancet-1
-.025 -.037
(.914) (.873)
Treated × Peer Performancet-1
-.087 .064
(.705) (.825)
Postregulation × Peer Performancet-1
-.248 .016
(.500) (.970)
Treated × Postregulation × Peer Performancet-1
.127 -.462
(.738) (.350)
Peer Performancet
-.324 -.259
(.154) (.414)
Treated × Peer performancet
.145 .030
(.539) (.931)
Postregulation × Peer Performancet
.598 .492
(.143) (.357)
40
03

41. Table
6:
Panel
B
Change
in
disclosure
regime:
difference-in-differences
analysis
Panel B. Difference-in-differences regressions
Dependent variable: Whether a candidate peer is chosen as a performance peer by an RPE granting firm
(1) (2) (3) (4)
Treated × Postregulation × Peer performancet
-.595 -.587
(.169) (.312)
Peer correlation 2.546*** 2.544***
(.000) (.000)
Match on industry 3.537*** 3.535***
(.000) (.000)
Match on assets 1.502*** 1.504***
(.000) (.000)
Match on leverage 0.903*** 0.901***
(.000) (.000)
Match on S&P 500 0.381 0.384
(.204) (.204)
Match on business segments 1.378*** 1.382***
(.000) (.000)
Match on geographic segments 0.336** 0.335**
(.049) (.049)
Number of peers 0.073*** 0.073***
(.000) (.000)
N 275,611 275,611 275,611 275,611
Pseudo R2 .000 .360 .001 .360
41
03

42. New Rules Same Results
● Pretreatment characteristics are similar between the initial test and
the DID estimation, minimizing the likelihood of unobservable
differences driving results.
● Under DID estimation, Treated × Post × Peer performancet-1
is
statistically insignificant.
● The results suggest that enhanced disclosure rules of RPE contracts
did not mitigate the tendency to select underperforming peers.
42
02

43. Placebo Test
● Can our test detect a change in the performance peer selection
process? (1018)
○ We employ a difference-in-difference (DID) model:
Peer scoreijt
= Peer correlationijt−1
+ Match on industryijt−1
+ Match on assetsijt−1
+ Match on leverageijt−1
Peer scoreijt
= Peer correlationijt−1
+ Match on industryijt−1
+ Match on assetsijt−1
+ Match on leverageijt−1
+ Peer
performancej,t−1
○ 5 primary determinants, normalize returns between 0 and 1
○ Identify placebo peers
○ Control firms: no historical performance
○ Treated firms: include historical performance in pre period only.
○ Assume treated firms stop preferring underperforming peers.
● By using a fake treatment group (firms not affected by the program), the placebo test revealing zero
impact supports an equal-trend assumption. 43
02

44. Table
7
(1)
Change
in
disclosure
regime
–
Placebo
analysis
Dependent variable: Whether a candidate peer is chosen as a performance peer by an RPE granting firm
(1) (2)
Treated -.081 -.031
(.695) (.947)
Postregulation .057 .067
(.288) (.835)
Treated × Postregulation .051 .308
(.426) (.437)
Peer performancet-1
-.349 -.530*
(.104) (.051)
Treated × Peer performancet-1
-.965*** -4.823***
(.001) (.000)
Postregulation × Peer performancet-1
.162 .613
(.619) (.242)
Treated × Post × Peer performancet-1
.923** 3.841***
(.011) (.000)
Peer correlation 8.611***
(.000)
44
03

45. Table
7
(2)
Change
in
disclosure
regime
–
Placebo
analysis
Dependent variable: Whether a candidate peer is chosen as a performance peer by an RPE granting firm
(1) (2)
Match on industry 6.210***
(.000)
Match on assets 6.899***
(.000)
Match on leverage 6.308***
(.000)
Match on S&P 500 -0.526**
(.028)
Match on business segments 0.622*
(.057)
Match on geographic segments 0.453
(.224)
Number of peers 0.124***
(.000)
Year fixed effects No No
Clustered standard errors Firm & Peer Firm & Peer
N 275,611 275,611
Pseudo R2 .006 .765
45
03

46. Placebo Test
● Observations
○ Under placebo test, Treated × Post × Peer performancet-1
is
positive and significant at the 1% level, suggesting that treated
firms are less likely to select weak peers after the regulatory
change.
○ The placebo test weakens the argument that lack of statistical
power drove the results of the DID estimation.
46
02

47. Other Arguments
● Did firms after 2006 just switch to stock indices from customized peer
groups or vice versa?
○ Logistic Difference-in-Difference regression
■ Control firms: used custom peer group or stock indices in 2005
and disclosed RPE
■ Treated: disclosed custom peer group or stock indices after
2006
○ Interaction term coefficient is statistically insignificant suggesting
enhanced disclosure did not impact peer group/indices selection.
● Did firms just drop RPE to avoid exposure?
○ Only 3 firms dropped RPE from 2006-2007, minimizing bias.
47
02

48. Conclusions
The take-away
04

49. Results & Limitations
● On average, firms choose stock indices for CEO RPE contracts for the following reasons:
○ Complex activities
○ Difficulty in choosing true peers
○ Busy and less independent directors.
● Confirmation of optimal contract theory predictions
○ Firms choose custom peer groups based on size, industry, leverage, historical
performance correlations, index membership, operational structure, and
geographical presence
● Confirmation of managerial power theory
○ Firms tend to choose underperforming performance peers.
○ Peer groups change over time both adding and retaining underperforming peers
● Effect of SEC’s 2006 disclosure ruling on the selection of performance peers
○ Compulsory disclosure did not impact tendency to select underperforming peers
● Limitations
○ Contract CEO RPE terms are co-determined
■ Performance peer types, performance measures, performance targets, etc.
○ Firm characteristics and contractual terms are co-determined
■ Contractual choices may impact firm characteristics and peer selection.
49

50. You are Amazing
Ask me all the questions you
desire. I will do my best to
answer honestly and strive to
grasp your intent and
creativity.

51. Research Questions
1. How do firms choose performance peer groups used in chief executive officer (CEO)
relative performance evaluation (RPE) contracts? (997)
2. Do factors supported by managerial power theory also contribute to predicting the
choice of performance peer firms? (998)
3. Do enhanced disclosure requirements affect the tendency of firms to select
underperforming peers? (999)
4. How do firms choose their performance peer group? (1003)
5. What determines the choice between a custom peer group and a stock index as the type
of performance peer group for an RPE granting firm? (1004)
6. How do custom peer group users choose their performance peers? (1006)
7. Are firms actively changing their custom peer groups or is it merely the case that weak
firms already included in peer groups in 2006 have persistently underperformed during
our 6-year sample period? (1011)
8. Do underperforming RPE granting firms have a greater tendency to select weaker
performance peers? (1013)
9. Did enhanced disclosure change how performance peers Are selected? (1015)
10. Can our test detect a change in the performance peer selection process? (1018)
51
02