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Why do larger firms pay executives more for
performance?
Performance-based versus labor market incentives
VU Finance Lunch Seminar
Bo Hu
October 26, 2018
Department of Economics, Vrije Universiteit Amsterdam
Tinbergen Institute
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Introduction
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Introduction
• Industry: Competition for executive matters for incentive contracts.
• Apple proxy statement 2016:
“experienced personnel ... are in high demand, ... (the contract
incentives are designed) to attract and retain a talented executive
team and align executives interests with those of shareholders ...”
• Amazon proxy statement 2016:
The core philosophy concerning executive incentive package is “to
attract and retain the highest caliber employees”
• ...
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Introduction
• Academia: The mechanism linking the managerial labor market and
incentive contract design is not clear.
• Direction for future research in Edmans et al. 2017
“Most models of incentives in market equilibrium are static. It would
be useful to add a dynamic moral hazard problem where incentives
can be provided not only through contracts, but also by ... the
promise of being hired by a larger firm. This would, among other
things, analyze how contracting incentives interact with ... hiring
incentives. These different incentive channels may conflict with as
well as reinforce each other.”
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Research Questions
• How does the managerial labor market competition impact the
incentive contracts?
• Explain two important empirical puzzles
1. Firm-size premium in compensation growth
Compensation growth is higher in larger firms, controlling for total
compensation at the beginning.
2. Firm-size premium in performance-based incentives
Performance-based incentives are higher in larger firms controlling for
total compensation.
3
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Motivating Facts
• A typical executive compensation package:
total pay = salary + performance-based pay
(tdc1) (bonus, stocks, options, etc.)
30% 70%
• Performance-based incentives
delta =∆Wealth(in dollars)
∆Firm Value(in percentage)
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Research Questions
• How does the managerial labor market competition impact the
incentive contracts?
• Explain two important empirical puzzles
1. Firm-size premium in compensation growth
Compensation growth is higher in larger firms, controlling for total
compensation at the beginning.
2. Firm-size premium in performance-based incentives
Performance-based incentives are higher in larger firms controlling for
total compensation.
8
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Model
• embed dynamic moral hazard into an equilibrium search framework
• managerial labor market: search frictional and on-the-job search
• executives are poached by outside firms, and poaching offers have
impacts on compensation level and contract incentives
• a hierarchical job ladder towards larger firms
Explain firm-size premium in compensation growth
• executives use poaching offers to renegotiate with the current firm
• larger firms are more capable of countering outside offers
9
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Model
• embed dynamic moral hazard into an equilibrium search framework
• managerial labor market: search frictional and on-the-job search
• executives are poached by outside firms, and poaching offers have
impacts on compensation level and contract incentives
• a hierarchical job ladder towards larger firms
Explain firm-size premium in compensation growth
• executives use poaching offers to renegotiate with the current firm
• larger firms are more capable of countering outside offers
9
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Explain firm-size premium in performance-based incentives
1. Poaching offers generate labor market incentives
• poaching firms are willing to bid higher for more productive executive
• executive productivity depends on past effort
• taking effort today will lead to a more favorable offer from the same
poaching firm
2. Total Incentives = Performance-based + Labor Market Incentives
3. Labor Market Incentives decrease in firm size
• executives in larger firms are less likely to receive competitive outside
offers
• executives in larger firms have a higher certainty equivalent of
expected utility in the future; subjectively they are less sensitive to
wealth variation (diminishing marginal utility)
10
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Explain firm-size premium in performance-based incentives
1. Poaching offers generate labor market incentives
• poaching firms are willing to bid higher for more productive executive
• executive productivity depends on past effort
• taking effort today will lead to a more favorable offer from the same
poaching firm
2. Total Incentives = Performance-based + Labor Market Incentives
3. Labor Market Incentives decrease in firm size
• executives in larger firms are less likely to receive competitive outside
offers
• executives in larger firms have a higher certainty equivalent of
expected utility in the future; subjectively they are less sensitive to
wealth variation (diminishing marginal utility)
10
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Explain firm-size premium in performance-based incentives
1. Poaching offers generate labor market incentives
• poaching firms are willing to bid higher for more productive executive
• executive productivity depends on past effort
• taking effort today will lead to a more favorable offer from the same
poaching firm
2. Total Incentives = Performance-based + Labor Market Incentives
3. Labor Market Incentives decrease in firm size
• executives in larger firms are less likely to receive competitive outside
offers
• executives in larger firms have a higher certainty equivalent of
expected utility in the future; subjectively they are less sensitive to
wealth variation (diminishing marginal utility)
10
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Road Map
1. Model
2. Reduced-form Evidence
3. Structural Estimation
4. Two Counterfactual Analysis
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Related Literature
• Assignment Models
• Edmans, Gabaix and Landier (2009), Edmans and Gabaix (2011)
• executives in larger firms value leisure more u(w × g(e)).
• Moral Hazard Models
• Margiotta and Miller (2000), Gayle and Miller (2009), Gayle, Golan
and Miller (2015)
• moral hazard problem is more severe / the quality of signal (about
effort) is poor in larger firms
• Dynamic contract literature
• moral hazard: Spear and Srivastava (1987), etc.
• limited commitment: Thomas Worrall (1988, 1990), etc.
• Labour search literature
• sequential auction: Postel-Vinay and Robin (2002), etc.
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The Model
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Set Up: Moral Hazard
Discrete time and infinite periods
Executives:
• risk averse, u(w)− c(e), e ∈ {0, 1}, c(1) = c , c(0) = 0,
u(w) =w1−σ
1− σ• effort e stochastically increases executive productivity z ∈ Z• z is persistent, follows a discerete Markov Chain process
• Γ(z ′|z) when take the effort, Γs(z ′|z) when shirk
• die with δ ∈ (0, 1), the match breaks up, the job disappears
Firms:
• firm size s ∈ S, exogenous and permanent
• production (cash flow) y(s, z) = α0sα1z , α0, α1 ∈ (0, 1].
13
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Set Up: Moral Hazard
Discrete time and infinite periods
Executives:
• risk averse, u(w)− c(e), e ∈ {0, 1}, c(1) = c , c(0) = 0,
u(w) =w1−σ
1− σ• effort e stochastically increases executive productivity z ∈ Z• z is persistent, follows a discerete Markov Chain process
• Γ(z ′|z) when take the effort, Γs(z ′|z) when shirk
• die with δ ∈ (0, 1), the match breaks up, the job disappears
Firms:
• firm size s ∈ S, exogenous and permanent
• production (cash flow) y(s, z) = α0sα1z , α0, α1 ∈ (0, 1].
13
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Set Up: Managerial Labor Market
Managerial Labor Market:
• search frictional and allows on-the-job search
• with λ1 ∈ (0, 1) sample an outside firm s ′ from F (s ′)
Sequential Auction:
• Bertrand competition between current firm s and outside firm s ′
• Each firm has a bidding frontier, W (z , s), defined by
Π(z , s,W (z , s)
)= 0
• W (z , s) increases in z and s
• if s ′ < s, renegotiate with the current firm
• if s ′ > s, transit to the poaching firm
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Contracting Problem
Firms maximize profits
Π(z , s,V ) = maxw ,W (z′,s′)
∑z′∈Z
∑s′∈S
[y(s, z ′)− w + β̃Π(z ′, s,W (z ′, s ′))
]F̃ (s ′)Γ(z ′|z)
subject to
V = u(w)− c + β̃∑z′∈Z
∑s′∈S
W (z ′, s ′)F̃ (s ′)Γ(z ′|z), (PKC)
β̃∑z′∈Z
∑s′∈S
W (z ′, s ′)F̃ (s ′)(
Γ(z ′|z)− Γs(z ′|z))≥ c , (IC)
W (z ′, s ′) ≥ min{W (z ′, s ′),W (z ′, s)}, (PC-Executive)
W (z ′, s ′) ≤W (z ′, s). (PC-Firm)
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The Equilibrium
An stationary equilibrium is defined by
• value functions {W 0,W ,Π};• optimal contracts σ = {w , e,W (z ′)} for z ′ ∈ Z;
• Γ follows the optimal effort choice;
• a distribution of executives across employment states evolving
according to flow equations.
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The Optimal Contract
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
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The Optimal Contract
wage
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The Optimal Contract
wage
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
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induced by sequential auctionwith outside firm
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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The Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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Explain size premium in
compensation growth
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Three sets of poaching offers
Three sets of outside firms s ′:
M1 : s ′ ≥ s, lead to job turnovers
M2 : s ′ < s, improve compensation, no job turnovers
M3 : other or no outside firms
The continuation value of an executive is∑s′∈M1
F (s ′)E[W (z ′, s)] +∑
s′∈M2
E[W (z ′, s ′)]F (s ′)︸ ︷︷ ︸labor market driven
+∑
s′∈M3
F (s ′)E[W (z ′)]︸ ︷︷ ︸promise driven
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Three sets of poaching offers
Three sets of outside firms s ′:
M1 : s ′ ≥ s, lead to job turnovers
M2 : s ′ < s, improve compensation, no job turnovers
M3 : other or no outside firms
The continuation value of an executive is∑s′∈M1
F (s ′)E[W (z ′, s)] +∑
s′∈M2
E[W (z ′, s ′)]F (s ′)︸ ︷︷ ︸labor market driven
+∑
s′∈M3
F (s ′)E[W (z ′)]︸ ︷︷ ︸promise driven
37
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s
s
s1
s(w)
M2 : ∆w > 0
M3 : ∆w = 0
38
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s
s
s1
s(w)
s
s
s2
s(w)
M2 : ∆w > 0
M3 : ∆w = 0
M2 : ∆w > 0
M3 : ∆w = 0
39
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s
s
s1
s(w)
s
s
s2
s(w)
M2 : ∆w > 0
M3 : ∆w = 0
M2 : ∆w > 0
M3 : ∆w = 0
40
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s
s
s1
s(w)
s
s
s2
s(w)
M2 : ∆w > 0
M3 : ∆w = 0
M2 : ∆w > 0
M3 : ∆w = 0
41
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Explain size premium in
performance-based incentives
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Incentive Compatibility Constraint
What is the incentive out of W (z ′)?
I[W (z ′)] ≡ β̃
{∑z′
W (z ′)Γ(z ′|z)−∑z′
W (z ′)Γs(z ′|z)
}.
The incentive compatibility constraint is∑s′∈M1
F (s ′)I[W (z ′, s)] +∑
s′∈M2
I[W (z ′, s ′)]F (s ′)︸ ︷︷ ︸Labor Market Incentives
+∑
s′∈M3
F (s ′)I[W (z ′)]︸ ︷︷ ︸Performance-based Incentives
≥ c .
Sets of outside firms s ′:
M1 : s ′ ≥ s, lead to job turnovers
M2 : s ′ < s, improve compensation, no job turnovers
M3 : other or no outside firms
42
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Incentive Compatibility Constraint
What is the incentive out of W (z ′)?
I[W (z ′)] ≡ β̃
{∑z′
W (z ′)Γ(z ′|z)−∑z′
W (z ′)Γs(z ′|z)
}.
The incentive compatibility constraint is∑s′∈M1
F (s ′)I[W (z ′, s)] +∑
s′∈M2
I[W (z ′, s ′)]F (s ′)︸ ︷︷ ︸Labor Market Incentives
+∑
s′∈M3
F (s ′)I[W (z ′)]︸ ︷︷ ︸Performance-based Incentives
≥ c .
Sets of outside firms s ′:
M1 : s ′ ≥ s, lead to job turnovers
M2 : s ′ < s, improve compensation, no job turnovers
M3 : other or no outside firms
42
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Incentive Compatibility Constraint
What is the incentive out of W (z ′)?
I[W (z ′)] ≡ β̃
{∑z′
W (z ′)Γ(z ′|z)−∑z′
W (z ′)Γs(z ′|z)
}.
The incentive compatibility constraint is∑s′∈M1
F (s ′)I[W (z ′, s)] +∑
s′∈M2
I[W (z ′, s ′)]F (s ′)︸ ︷︷ ︸Labor Market Incentives
+∑
s′∈M3
F (s ′)I[W (z ′)]︸ ︷︷ ︸Performance-based Incentives
≥ c .
Sets of outside firms s ′:
M1 : s ′ ≥ s, lead to job turnovers
M2 : s ′ < s, improve compensation, no job turnovers
M3 : other or no outside firms
42
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s
s
s1
s(w)
M1 : I[W (z′, s1)]
M2 : I[W (z′, s′)]
M3 : 0
43
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s
s
s1
s(w)
s
s
s2
s(w)
M1 : I[W (z′, s2)]
M2 : I[W (z′, s′)]
M3 : 0
M1 : I[W (z′, s1)]
M2 : I[W (z′, s′)]
M3 : 0
44
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s
s
s1
s(w)
s
s
s2
s(w)
M1 : I[W (z′, s2)]
M2 : I[W (z′, s′)]
M3 : 0
M1 : I[W (z′, s1)]
M2 : I[W (z′, s′)]
M3 : 0
45
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s
s
s1
s(w)
s
s
s2
s(w)
M1 : I[W (z′, s2)]
M2 : I[W (z′, s′)]
M3 : 0
M1 : I[W (z′, s1)]
M2 : I[W (z′, s′)]
M3 : 0
>
>
>
=
=
46
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Incentives from W (z ′, s) decrease in s
s1 ×∆z s2 ×∆z
u
w
I[W (z′, s2)]
I[W (z′, s1)]
47
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Incentives from W (z ′, s) decrease in s
Proposition
Suppose the executives’ utility is of the CRRA form and the cost of effort
c = c(s), then I(W (z ′, s)
)decreases in s if
σ > 1 +s1−α1
α1ψ′(s), (1)
where ψ(s) is a function of s that is positive and increasing in s.
Intuition
• a higher s leads to higher certainty equivalent of W (z ′, s)
• a higher certainty equivalent leads to lower marginal utility of extra
wealth
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Summary
• How does the managerial labor market competition impact the
incentive contracts?
Competition impacts both compensation level and incentives.
• Explain two important empirical puzzles
1. Firm-size premium in compensation growth
Larger firms are more capable of countering outside offers.
2. Firm-size premium in performance-based incentives
Poaching offers generate labor market incentives which decrease in
firm size.
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Examine Direct Evidence
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Three implications of the model
1. The managerial labor market is active.
2. Managers climb job ladders towards larger firms.
3. Managers in larger firms tend to have less job-to-job transitions.
50
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Data
Data sources
• ExecuComp: compensation and individual features, etc.
• CompuStat: firm performance, etc.
• CRSP: stock return.
• BoardEX: executive employment history.
Define job turnovers
• Job-to-job transition: leaves the current firm, and starts to work in
another firm within 180 days.
• Exit: otherwise.
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Three implications of the model
1. The managerial labor market is active.
2. Managers climb job ladders towards larger firms.
3. Managers in larger firms tend to have less job-to-job transitions.
52
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Job-to-job transition rate over age
30 35 40 45 50 55 60 65 70 75Age (years)
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
Job-
to-J
ob T
rans
ition
Rat
e (%
)
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Exit rate over age
30 35 40 45 50 55 60 65 70 75Age (years)
0.02
0.04
0.06
0.08
0.10
0.12
0.14
Exit
Rat
e (%
)
54
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Key implications of the model
1. The managerial labor market is active.
2. Managers climb job ladders towards larger firms.
3. Managers in larger firms tend to have less job-to-job transitions.
55
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Climb the Job Ladder
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Key implications of the model
1. The managerial labor market is active.
2. Managers climb job ladders towards larger firms.
3. Managers in larger firms tend to have less job-to-job transitions.
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58
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Estimation
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Model Specifications
• utility function of CRRA form
u(w) =w1−σ
1− σ
• production function (cash flows)
y(s, z) = eα0sα1z
• productivity process by AR(1), discretized by Tauchen (1989)
zt = ρ0(e) + ρzzt−1 + εt
• poaching firm distribution by truncated log-normal F (s)
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Parameters
Parameters Description
δ the death probability
λ1 the offer arrival probability
ρz the AR(1) coefficient of productivity shocks
µz the mean of productivity shocks for e = 1
σz the standard deviation of productivity shocks
µs the mean of F(s)
σs the standard deviation of F(s)
c cost of efforts
σ relative risk aversion
α0, α1 production function parameters
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Moments and Estimation
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Predictions on the empirical puzzles
• These moments are not targeted.
• They are predicted by the estimated model.
• The model quantitatively captures the two premiums.
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Two Counterfactual Analysis
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1. If labor market incentives are ignored ...
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2. Spillover effects
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2. Spillover effects
67
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Conclusion
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Conclusion
• Managerial labor market competition impacts the incentive contracts
on both compensation level and incentives.
• Larger firms are more capable of countering outside offers.
• Poaching offers generate labor market incentives which decrease in
firm size.
• Structure estimates show the model captures the firm size premium
in compensation growth and performance-based incentives.
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No Moral Hazard, Full Commitment
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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Only Moral Hazard
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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Only Limited Commitment
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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Optimal Contract
wage
t0 1 2 3 4 5 6 7 8 9 10 11 12
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CEO’s of "Small Firms" in S&P 500
+-----------------------------------------------------------------+
tdc1: total compensation
delta: dollar-percentage incentive
+-----------------------------------------------------------------+
| Company Market Cap tdc1 delta |
| millions 000’s 000’s/%|
|-----------------------------------------------------------------|
| INCYTE CORP 446.408 2432.9734 60.939838 |
| WESTROCK CO 547.828 2800.668 130.96215 |
| ENVISION HEALTHCARE CORP 678.6906 1777.991 217.729 |
| PRICELINE GROUP INC 886.0817 1775.531 165.73476 |
| LKQ CORP 889.9763 2602.093 473.70974 |
| REGENERON PHARMACEUTICALS 897.3801 3094.134 566.14187 |
| SKYWORKS SOLUTIONS INC 1113.547 2638.243 128.10688 |
| CENTENE CORP 1130.155 4584.605 344.02299 |
| ALASKA AIR GROUP INC 1194.977 950.098 99.525198 |
| HOLOGIC INC 1276.448 2709.708 428.10996 |
| ACUITY BRANDS INC 1328.171 1102.528 133.42285 |
| ANSYS INC 1368.129 3738.803 431.01562 |
| GARTNER INC 1474.909 8945.338 158.65569 |
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CEO’s of "Large Firms" in S&P 500
+-----------------------------------------------------------------+
tdc1: total compensation
delta: dollar-percentage incentives
+-----------------------------------------------------------------+
| Company Market Cap tdc1 delta |
| millions 000’s 000’s/%|
|-----------------------------------------------------------------|
| TIME WARNER INC 79965.89 18545.215 1212.9513 |
| CONOCOPHILLIPS 80163.26 35442.729 4520.5571 |
| UNITED PARCEL SERVICE INC 82439.55 3120.042 340.01132 |
| VERIZON COMMUNICATIONS INC 83233.88 19425 861.09722 |
| HOME DEPOT INC 86128.2 35750.103 2014.3633 |
| AT&T INC 94944.89 17283.529 1666.3201 |
| COCA-COLA CO 95494.39 12781.61 425.62199 |
| PEPSICO INC 97836.48 15268.415 2919.7995 |
| CISCO SYSTEMS INC 121238.6 16269.85 5981.3853 |
| CHEVRON CORP 126749.6 13125.882 1106.8351 |
| INTL BUSINESS MACHINES CORP 129381.2 21693.615 1298.8777 |
| INTEL CORP 147738.2 6101.835 1874.5755 |
| WAL-MART STORES INC 192048.2 16652.894 1465.7708 |
| EXXON MOBIL CORP 344490.6 48922.808 3843.027 |
![Page 93: Why do larger rms pay executives more for performance? - Bo Hubohuecon.github.io/docs/vu_finance.pdf · Assignment Models Edmans, Gabaix and Landier (2009), Edmans and Gabaix (2011)](https://reader034.vdocument.in/reader034/viewer/2022052102/603bfeba4a18d67b4d0197ed/html5/thumbnails/93.jpg)
References i
References
Edmans, Alex, Xavier Gabaix, and Dirk Jenter (2017), “Executive
compensation: A survey of theory and evidence.” Technical report,
National Bureau of Economic Research.