Information Disclosure and Corporate Governance
Benjamin E. Hermalin1
1 University
2 Ohio
Michael S. Weisbach2
of California, Berkeley
State University
Talk at
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Disclosure & Governance
Copyright © 2010 Benjamin E.
Hermalin & Michael S. Weisbach.
All rights reserved.
May 27, 2013
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Introduction
Better Corporate Disclosure a Long-Sought Reform
1927: William Z. Ripley, Main Street and Wall Street
1932: Adolph A. Berle & Gardiner C. Means, The Modern
Corporation and Private Property
1930s: Various reform legislation in wake of Great Depression
..
.
2002: Sarbanes-Oxley
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Introduction
An International Phenomenon
UK: Cadbury Report, 1992.
Japan: major reforms in 2002.
Australia: CLERP 9, 2004.
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Introduction
Focus of Reform: Increased Transparency
Is Increased Transparency a Good Thing?
General view is more disclosure ⇒ better governance.
Some empirical evidence suggests that firms that disclose more
perform “better.”
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Introduction
Potential Problem Interpreting Empirical Evidence:
Performance
Firm 2
Firm 1
L
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H
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Amount Disclosed
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Introduction
Potential Problem Interpreting Empirical Evidence:
Performance
Regression line
Firm 2
Firm 1
L
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H
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Amount Disclosed
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Introduction
Potential Problem Interpreting Empirical Evidence:
Analyzing an Equilibrium Phenomenon
Performance
Regression line
Firm 2
Firm 1
L
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H
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Amount Disclosed
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Introduction
What This Paper’s About
Why could there be a tradeoff between disclosure (transparency) and
performance?
What factors influences this tradeoff?
What are the consequences of more disclosure for corporate
governance (agency problems)?
More disclosure ⇒ Greater managerial compensation in equilibrium.
More disclosure ⇒ More managerial turnover in equilibrium.
More disclosure ⇒ Changes to managerial actions in equilibrium.
. . . including potentially greater managerial myopia.
. . . including potentially greater conservatism.
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Introduction
Outline of Talk
1
Introduction
2
Model
3
General Analysis
4
Governance Models
5
General Equilibrium
6
Additional Discussion & Conclusions
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Model
Timing
The Model
Basic Timing
Owners
(principal)
set disclosure
regime.
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Model
Timing
The Model
Basic Timing
Owners
(principal)
set disclosure
regime.
Owners
negotiate
with & hire
ceo (agent)
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Model
Timing
The Model
Basic Timing
Owners
(principal)
set disclosure
regime.
Information
is revealed,
the quality of
which
depends on
disclosure
regime
Owners
negotiate
with & hire
ceo (agent)
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Model
Timing
The Model
Basic Timing
Owners
(principal)
set disclosure
regime.
Information
is revealed,
the quality of
which
depends on
disclosure
regime
Owners
negotiate
with & hire
ceo (agent)
Hermalin & Weisbach (Berkeley & OSU)
Owners base
an action
(e.g.,
dismissal) on
information
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Model
Timing
The Model
Basic Timing
Owners
(principal)
set disclosure
regime.
Information
is revealed,
the quality of
which
depends on
disclosure
regime
Owners
negotiate
with & hire
ceo (agent)
Hermalin & Weisbach (Berkeley & OSU)
Payoffs
realized.
Owners base
an action
(e.g.,
dismissal) on
information
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Model
Examples
Examples
Owners learn information about ceo’s ability. Consequent action is
whether owners keep or fire ceo. The ceo suffers a loss if fired.
Information: firm prospects. Consequent action: add or subtract
resources invested. The ceo prefers to manage more resources than
less ceteris paribus.
Information: lessens ceo’s informational advantage. Consequent
action: adjustment to ceo’s compensation plan. The ceo loses
information rents.
Information: performance more informative. Consequent action:
adjustment to ceo’s compensation plan. The ceo loses quasi-rents.
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Model
Payoffs
Notation and Payoffs
D denotes disclosure regime.
D ≻ D ′ denotes D more informative than D ′ .
w denotes ceo compensation.
Owners’ payoff = π(D) − w .
CEO’s payoff = U(D) + v (w ); v ′ (·) exists and is positive.
CEO cannot buy his job; hence, w ≥ 0.
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Model
Payoffs
Differing Preferences
Condition
If D and D ′ are two disclosure regimes such that D ≻ D ′ , then
π(D) ≥ π(D ′ ) and U(D) < U(D ′ ).
At the moment this is an assumption. Later will prove it holds in games
of interest.
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Model
Bargaining
Setting Compensation
Generalized Nash Bargaining
Assume compensation, w , set through generalized Nash bargaining.
That is, w set to maximize
λ log π(D) − w + (1 − λ) log U(D) + v (w ) − ū ,
where
λ = owners’ bargaining power, λ ∈ [0, 1]; and
ū is the value of the ceo’s outside option (e.g., utility if he retires).
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General Analysis
Bargaining Comparative Statics
The Basic Tradeoff
Proposition
Assume wage bargaining is generalized Nash and the Condition holds.
Then the ceo’s compensation, as determined by the bargaining process, is
non-decreasing in how informative is the disclosure regime.
[The talk ignores corner solutions (i.e., worlds in which ceos receive 0
compensation).]
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General Analysis
Bargaining Comparative Statics
Proof of Proposition 1
Non-extreme bargaining (i.e., 0 < λ < 1)
bargain power
surplus
(1−λ)v ′ (w )
U(D)+v(w )−ū
v −1 ū−U(D)
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λ
π(D)−w
we
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π(D)
w
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General Analysis
Bargaining Comparative Statics
Proof of Proposition 1
Non-extreme bargaining: Better disclosure =⇒ red curve shifts up
bargain power
surplus
(1−λ)v ′ (w )
U(D)+v (w )−ū
we
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w
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General Analysis
Bargaining Comparative Statics
Proof of Proposition 1
Non-extreme bargaining: Better disclosure =⇒ blue curve shifts down
bargain power
surplus
λ
π(D)−w
we
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we
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w
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General Analysis
Bargaining Comparative Statics
Proof of Proposition 1
Non-extreme bargaining (i.e., 0 < λ < 1): Better disclosure
bargain power
surplus
we
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we
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w
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General Analysis
Bargaining Comparative Statics
Proof of Proposition 1
Extreme bargaining (i.e., λ = 1 or = 0)
If owners have all the
bargaining power: U(D) + v (w ) = ū; hence,
w = v −1 ū − U(D) .
If ceo has all the bargaining power: π(D) − w = 0; hence,
w = π(D).
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General Analysis
Bargaining Comparative Statics
Why Might CEOs Resist Improved Disclosure?
Proposition
Assume wage bargaining is generalized Nash and the Condition holds.
Assume, too, that neither party has all the bargaining power (i.e., assume
λ ∈ (0, 1)). Finally, assume the ceo’s utility exhibits non-increasing
marginal utility of income (i.e., assume ceo is risk neutral or risk averse in
income). If there is a reform to disclosure that results in a disclosure
regime that is more informative than the one the owners would have
chosen, then the ceo’s expected total utility is reduced.
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General Analysis
Bargaining Comparative Statics
Proof of Proposition 2
Part I
Let D ∗ be the owners’ unconstrained choice and D r the reform level.
By assumption D r ≻ D ∗ .
Let w (D) denotes equilibrium compensation given disclosure regime.
Objective is to show U(D ∗ ) + v w (D ∗ ) > U(D r ) + v w (D r ) .
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General Analysis
Bargaining Comparative Statics
Proof of Proposition 2
Part II
First-order from general Nash bargaining tell us
(1 − λ)v ′ w (D)
λ
+
= 0.
−
π(D) − w (D) U(D) + v w (D) − ū
(⋆)
D r 6= D ∗ =⇒
π(D r ) − w (D r ) < π(D ∗ ) − w (D ∗ ) .
Proposition 1 =⇒ w (D r ) > w (D ∗ ).
Therefore: U(D r ) + v w (D r ) < U(D ∗ ) − v w (D ∗ ) .
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General Analysis
Bargaining Comparative Statics
What if More Disclosure Just Makes Being CEO a Worse
Job?
Suppose ū reflects next best ceo job.
If U(D) goes down, perhaps ū should go down too.
To reflect that possibility, suppose U(D) − ū(D) ≡ ∆.
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General Analysis
Bargaining Comparative Statics
Compensation Still Rises
Proposition
Assume the owners’ gross expected profit, π(·), is strictly increasing in the
informativeness of the disclosure regime (i.e., D ≻ D ′ ⇒ π(D) > π(D ′ ))
and that bargaining is generalized Nash. Suppose that the ceo’s gross
expected utility from the job, U(·), decreases one-for-one with his outside
option as disclosure is made universally more informative. Then an
increase in the level of disclosure causes an increase in the ceo’s
compensation unless the owners have all the bargaining power, in which
case his compensation is unaffected.
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General Analysis
Bargaining Comparative Statics
Proof of Proposition 3
bargain power
surplus
(1−λ)v ′ (w )
∆+v(w )
v −1 ∆
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λ
π(D)−w
we
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π(D)
w
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General Analysis
Bargaining Comparative Statics
Proof of Proposition 3
bargain power
surplus
(1−λ)v ′ (w )
∆+v(w )
v −1 ∆
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we
we
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w
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Governance Models
Learning Models
Need to Justify Condition
Learning Models
Suppose owners’ payoff is r γ(a) − c(a), where
a is owners’ action;
r is a stochastic return; and
γ(·) and c(·) functions.
E{r } = θ.
θ is an unknown parameter.
From information owners receive, they form an unbiased estimate θ̂.
How good an estimate depends on disclosure regime.
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Governance Models
Learning Models
Learning Models
Examples
Parameter θ is ceo’s ability (or monotonic transformation thereof).
Action is fire ceo (a = 1) or keep (a = 0). (Alternatively, a = 1 ⇒
sell to acquirer; a = 0 ⇒ reject acquirer.)
c(1) > c(0) (i.e., firing costs) and γ(a) = 1 − a .
Or parameter θ reflects firm’s future prospects. Action is to adjust
capital in firm (a > 0 is adding, a < 0 is subtracting).
c(a) =
a2
(i.e., quadratic adjustment costs) and γ(a) = K + a ,
2
where K is baseline capital in firm.
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Governance Models
Learning Models
Learning Models
Owners’ Actions and Payoffs
Given θ̂, owners choose a to maximize θ̂γ(a) − c(a).
Let a∗ (θ̂) be solution.
Owners’ expected payoff conditional
on θ̂ is, thus,
∗
∗
Π(θ̂) = θ̂γ a (θ̂) − c a (θ̂) .
Lemma
The owners’ payoff function Π(·) is convex.
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Governance Models
Learning Models
Owners’ Choice of Action
Proof of Lemma
$
θ̂γ a∗ (θ̃) − c a∗ (θ̃)
Π(θ̃)
θL
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θ̃
θR
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θ̂
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Governance Models
Learning Models
Owners’ Choice of Action
Proof of Lemma (continued)
$
θ̂γ a∗ (θ̃) − c a∗ (θ̃)
Π(θ̃)
θL
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θ̃
θR
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θ̂
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Governance Models
Learning Models
Owners’ Choice of Action
Proof of Lemma (continued)
$
Π(θ̂)
Π(θ̃)
θL
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θ̃
θR
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θ̂
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Governance Models
Learning Models
Information and Risk
Ex ante the estimator θ̂ is a random variable.
Result from statistics: If D ≻ D ′ in the sense of Blackwell
informativeness, then the distribution of θ̂(D) is a mean-preserving
spread of the distribution of θ̂(D ′ ).
That is, θ̂(D) is riskier than θ̂(D ′ ) in the sense of second-order
stochastic dominance.
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Governance Models
Learning Models
Owners Like More Informative Disclosure Regimes
From Lemma, owners’ payoff is convex in θ̂; that is, they are risk
loving.
From previous slide, more informative ⇒ riskier.
Hence, owners must prefer more informative disclosure regimes to less
informative ceteris paribus.
In other words, owners’ “part” of the Condition is met.
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Governance Models
Learning Models
The Dismissal Model
Consider the dismissal model outlined earlier.
CEO’s utility is
u(θ̂) =
Hermalin & Weisbach (Berkeley & OSU)
−ℓ , if θ̂ < −c(1)
.
0 , if θ̂ ≥ −c(1)
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Governance Models
Learning Models
The Dispersive Order
Let F (·|D) be the distribution function for θ̂ conditional on the
disclosure regime.
Distribution F (·|D ′ ) dominates F (·|D) in the sense of the dispersive
≥
F (·|D)) if
order (denoted F (·|D ′ ) disp
F −1 (ξ|D ′ ) − F −1 (ξ ′ |D ′ ) < F −1 (ξ|D) − F −1 (ξ ′ |D)
whenever 1 > ξ > ξ ′ > 0.
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Governance Models
Learning Models
The Dispersive Order
Red distribution dominates blue distribution in the dispersive order
1
ξ
ξ′
F −1
−1 ′
(ξ |D ′ )
(ξ ′ F
|D
)
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F −1 (ξ|D ′ )
F −1
(ξ
|D
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)
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Governance Models
Learning Models
The Dismissal Model
Opposing preferences
All distributions of θ̂ have the same mean.
≥
≥
Hence, F (·|D ′ ) disp
F (·|D) implies F (·|D ′ ) ssd
F (·|D).
≥
Previous analysis implies F (·|D ′ ) disp
F (·|D) means owners prefer D to
′
D.
CEO has opposite preferences:
Proposition
Suppose the median of the estimate θ̂ equals the mean and the mean
≥
exceeds firing cost. Then F (·|D ′ ) disp
F (·|D) implies the ceo prefers D ′ to
D. In other words, the Condition holds for the dismissal model.
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Governance Models
Learning Models
Proof of Proposition 6
≥
Result follows if F (·|D ′ ) disp
F (·|D) ⇒ F −c(1)D > F −c(1)D ′ .
≥
F (·|D ′ ) disp
F (·|D) implies
F −1 1/2D ′ − F −1 ξ D ′ < F −1 1/2D − F −1 ξ D
(†)
for all ξ < 1/2.
Mean and median coincide ⇒ F −1 1/2D ′ = F −1 1/2D .
Hence (†) implies, for all ξ < 1/2,
F −1 ξ D < F −1 ξ D ′ ⇒ F −1 F −c(1)D ′ D < −c(1)
⇒ F −c(1)D ′ < F −c(1)D ,
(recall F −c(1)D ′ < F E{θ̂}D ′ = 1/2 and distributions are
increasing functions).
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Governance Models
Learning Models
An Example Satisfying the Dispersive Order
A normal-learning-model version of the dismissal model
CEO ability, θ, is distributed normally with mean 0 and precision τ
(i.e., variance 1/τ ).
Information: owners observe a signal s, which is distributed normally
with a mean equal to ceo’s ability and a precision δ.
Hence, δ > δ′ means signal given δ more informative than signal
given δ′ ; that is, δ > δ′ corresponds to D ≻ D ′ .
Corollary
Consider the ceo-dismissal model. Suppose the estimate θ̂ is formed
according to the normal-learning model. Then mean and median of θ̂
coincide. If D is a more informative disclosure regime than D ′ , then
≥
F (·|D ′ ) disp
F (·|D). Hence, the owners prefer D to D ′ and the ceo prefers
D ′ to D. In other words, the Condition follows.
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Governance Models
Learning Models
More on Learning Models of Governance
Note that if the ceo’s utility were concave in θ̂, then the Condition
would hold.
Such would be the case, for instance, if ceo’s future wage were a
multiple of θ̂ and the ceo were risk averse in income.
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Governance Models
Learning Models
A Signal-Jamming Model
Recall example in which owners’ action was to add (a > 0) or
subtract (a < 0) resources/capital from firm.
Suppose ceos like to run bigger empires ceteris paribus.
Specifically, ceo’s utility (gross of compensation) is K + a, the size of
his empire.
Suppose, too, that the ceo can jam the owners’ information.
Specifically, ceo can take action x ∈ R+ such that owners see x θ̂
whenever θ̂ > 0 (when θ̂ < 0, they see θ̂).
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Governance Models
Learning Models
Signal-Jamming: A Heuristic Discussion
Graphical Interpretation
True distribution
0
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signal
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Governance Models
Learning Models
Signal-Jamming: A Heuristic Discussion
Graphical Interpretation
x
True distribution
Apparent distribution
signal
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Governance Models
Learning Models
Signal-Jamming: A Heuristic Discussion
Graphical Interpretation: In equilibrium no one fooled
x
Equilibrium distribution
Apparent distribution
−x̂
signal
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Governance Models
Learning Models
Signal-Jamming: A Heuristic Discussion
Graphical Interpretation: Red queen problem
−x̂
signal
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Governance Models
Learning Models
The Signal-Jamming Model: Continued
As noted, no one fooled in equilibrium.
That is, when statistic positive (i.e., x θ̂ > 0), owners will divide it by
xe , the value they anticipate ceo chooses in equilibrium.
Owners’ choice of a maximizes E{θ}(K + a) − a2 /2.
So choice of a when statistic positive is x θ̂/xe .
Condition for equilibrium is x = xe ; that is,
Z ∞
x
xe = argmax
θ̂dF (θ̂|D) − g (x) ,
x
e
e
0
(‡)
where g (·) is ceo’s cost-of-effort function, which is increasing and
convex.
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Governance Models
Learning Models
The Signal-Jamming Model: Continued
Employing integration by parts on (‡) and using the FOC, xe is
defined by
Z ∞
1 − F (θ̂|D) d θ̂ = xe g ′ (xe ) .
0
An increase in the left-hand side implies an increase in xe .
≥
If D ≻ D ′ in the Blackwell sense, then F (·|D ′ ) ssd
F (·|D), hence
Z ∞
Z ∞
1 − F (θ̂|D ′ ) d θ̂ .
1 − F (θ̂|D) d θ̂ >
0
0
Hence, xe increases as disclosure becomes more informative.
ceo’s equilibrium utility is −g (xe ), so ceo prefers a less informative
regime to a more informative regime ceteris paribus. We have shown:
Proposition
If D is a more informative disclosure regime than D ′ , then the owners
prefer D to D ′ and the ceo prefers D ′ to D. In other words, the
Condition holds.
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Governance Models
Learning Models
Signal-Jamming and the Dark Side of Disclosure
Suppose the action x directly or indirectly harmful to owners.
For instance, problem similar to Stein (1989) managerial myopia
story: x represents actions that boost earnings in short term in a
negative-NPV way relative to the long term.
Then see that one downside to greater disclosure is it could lead to
more harmful signal-jamming activities.
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Governance Models
Agency Models
Agency Models
Timing and Assumption
Owners
(principal)
set disclosure
regime.
Owners get
information
relevant to
design of
ceo bonus
plan.
Owners hire
ceo and his
base salary,
w , is set.
Hermalin & Weisbach (Berkeley & OSU)
ceo chooses
x and
receives
bonus, b,
according to
plan.
Owners set
the bonus
plan.
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Governance Models
Agency Models
Hidden-Information Agency
At last stage, before choosing action x, ceo only learns θ, a
payoff-relevant parameter.
θ ∈ {B, G }.
Before setting bonus plan, owners learn ψ = Pr{θ = B}. With
probability 1/2, ψ = δ + 1/2; and with probability 1/2, ψ = −δ + 1/2.
δ ∈ (0, 1/2) is the information structure (disclosure regime).
In what follows assume negative bonuses are not feasible.
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Governance Models
Agency Models
Mechanism Design and Information Rent
Bonus plan will be a mechanism: θ 7→ hx(θ), b(θ)i.
What is critical is the good type’s information rent: I x(B) , where
I (·) increasing and I (0) = 0. (Note I (·) is derived endogenously from
rest of model.)
Define X (ψ) = x(B) under owners’ optimal plan given
Pr{θ = B} = ψ.
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Governance Models
Agency Models
Hidden-Information Agency
Opposing preferences over disclosure
Proposition
If D is a more informative disclosure regime than D ′ (i.e., δ > δ′ ), then
the owners prefer D to D ′ . If the function mapping [0, 1]2 → R defined by
(ψ, ψ ′ ) 7→ ψI X (ψ ′ ) + ψ ′ I X (ψ) ,
is Schur concave, then the ceo prefers D ′ to D; that is, owners and ceo
have opposing preferences over disclosure regimes (i.e., the Condition
holds)
What is Schur Concavity?
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Governance Models
Agency Models
Hidden-Information Agency
An Example
Suppose owners’ payoff is x − y , where y is ceo’s total compensation.
Suppose ceo’s payoff is y − x 2 /kθ , where kG > kB > 0.
Then conditions of previous proposition can be shown to hold.
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Governance Models
Agency Models
Disclosure and Outrage
Lots of bad press about big payouts to ceos.
More disclosure could contribute to bigger payouts:
Proposition
Consider the hidden-information agency model. The maximum bonus that
can occur in equilibrium is greater the more informative is the disclosure
regime.
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Governance Models
Agency Models
Hidden-Action Agency
CEO utility is b − x C̄ , where x ∈ {0, 1} is hidden action taken in last
stage and C̄ > 0.
Owners’ payoff is R(x) − b, R(1) > R(0).
The realization R(x) is not verifiable.
If CEO “goofs off,” then owners detect this in a verifiable way with
probability δ.
No negative bonuses.
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Governance Models
Agency Models
Hidden-Action Agency
Readily shown that to induce ceo to choose x = 1, owners should
promise a bonus equal to C̄ /δ provided they don’t detect that he has
goofed off.
Detection of goofing off yields no bonus.
Owners’ equilibrium payoff is R(1) − C̄ /δ.
CEO’s equilibrium payoff is C̄ /δ − C̄ .
Hence,
Proposition
If D is a more informative disclosure regime than D ′ (i.e., δ > δ′ ), then
the owners prefer D to D ′ and the ceo prefers D ′ to D. That is, the
Condition holds.
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General Equilibrium
A General Equilibrium Model
Might worry that considering one firm in isolation.
Now consider a market model.
A continuum of firms, with each firm being indexed by β.
Equal measure of ceos, indexed by α.
Let α[i ] and β[i ] be, respectively, the i × 100 percentile of ceo type
and firm type.
Assume α[0] > 0.
Assume the distributions of α and β are twice continuously
differentiable so that α[·] and β[·] are as well. Both functions are
strictly increasing.
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General Equilibrium
Meaning of Type
CEO’s index, α, is his type. Assume it is observable.
Profit, gross of ceo compensation, is αΩ(δ, β).
Ω : R2 → R+ is twice continuously differentiable in each argument.
As a definition of firm type:
∂ 2 Ω(δ, β)
> 0.
∂δ∂β
(comp)
Assume better disclosure raises gross profit; that is, ∂Ω/∂δ > 0.
Assume higher type firms have greater profit ceteris paribus:
∂Ω/∂β > 0.
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General Equilibrium
CEO Utility and Total Welfare
CEO utility is w + h(δ).
Assume h(·) is a twice continuously differentiable function.
Consistent with the models above, assume h′ (δ) < 0.
Welfare is αΩ(δ, β) + h(δ).
For all α and β, assume the function defined by
δ 7→ αΩ(δ, β) + h(δ)
is globally concave in δ and has an interior maximum.
Global concavity implies this maximum is unique.
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General Equilibrium
Rest of Assumptions
In addition to working for one of the firms, a ceo can retire or pursue
some vocation other than being ceo.
His utility if he does so is u.
Firms make compensation offers and do so simultaneously.
Looking for an assortative-matching equilibrium.
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General Equilibrium
Equilibrium
Lemma
An assortative-matching equilibrium of the market described above exists
in which a firm of type β[i ] chooses disclosure regime δ[i ] , where δ[i ] solves
max α[i ] Ω δ, β[i ] + h(δ) .
δ
In this equilibrium, the i th ceo is paid
w[i ] = u − h(δ[i ] ) +
Z
0
i
Ω δ[j] , β[j] α̇[j] dj ,
(wage)
where α̇[j] = dα[j]/dj.
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General Equilibrium
Comparative Statics
Proposition
In equilibrium, a higher-type firm (e.g., a larger firm) has a greater level of
disclosure than a lower-type firm. Furthermore, a more able ceo earns
greater compensation, has greater utility, and works for a firm with more
stringent disclosure than a less able ceo.
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General Equilibrium
The Potential and Likely Unintended Consequences of
Reform
Proposition
Let δ[·] be the equilibrium disclosure schedule absent reform. If a reform is
imposed such that disclosure must be at least δ[ı̂] , where ı̂ ∈ (0, 1), and
this reform causes no firms to go out of business, then all ceos will see
their compensation increase in equilibrium and all but the least able ceo
will see his utility increase.
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Additional Discussion & Conclusions
Who Wants Reform?
In model above, neither owners nor ceo benefit from a binding
“reform” of disclosure.
But if we change timing to permit owners to lobby government after
agreeing to compensation but before subsequent compensation
negotiations, then owners have an incentive to do this.
The paper analyzes how this plays out and shows that if owners
cannot commit not to lobby, they will lobby.
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Additional Discussion & Conclusions
Some Empirical Implications
A consequence of imposing a binding disclosure reform on a firm
should lead to (i) increases in managerial pay; (ii) increase in the
turnover rate of top management; and (iii) a decrease in firm value.
Larger firms should have greater disclosure than smaller firms.
An increase in disclosure/information could lead to greater efforts at
signal boosting and more myopia.
An increase in disclosure could lead to greater managerial
conservatism.
Cross-sectionally, industries in which more information is released
about managerial performance (e.g., mutual funds) could see higher
pay and greater turnover rates than in industries in which less
information is released.
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Additional Discussion & Conclusions
Conclusions
Disclosure/transparency is not unambiguously desirable from the
perspective of good governance.
In a model of optimizing behavior, external reforms aimed at
increasing disclosure/transparency can be welfare reducing.
Importance of an equilibrium approach to governance: Just because
some policy is beneficial to owners ignoring equilibrium adjustments
doesn’t mean it is truly beneficial (i.e., once equilibrium adjustments
are taken into account).
Model has applications to other principal-agent relations.
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Additional Discussion & Conclusions
Schur Concavity
A symmetric function f : Rn → R, n ≥ 2, is Schur concave if
x majorizes x′ =⇒ f (x) < f (x′ ) .
What does “majorize” mean?
It essentially means the elements of the vector x are a
mean-preserving spread of the elements of the vector x′ .
For example (1, 3, 7, 9) majorizes (2, 4, 6, 8).
Back
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