A Dynamic Analysis of Misconduct in Contemporary Social Context
Tatsuhiko Inatani1

Kentaro Asai2

Abstract
Whereas many law literatures of punishment have addressed dynamic situation affected by thevery punishment in the future, the extant economic analysis of misconduct heavily relies on static
model. As the initial step toward the dynamic economic analysis of misconduct, our work models
the life-time wealth of a worker who faces the opportunity of wrongdoing and the risk of being
detected and suspended in order to characterize the deterrent effect of suspension on corporate
misconduct. Under the centralized economy, our model predicts raising a worker’s income stream
unambiguously improves social welfare by relaxing the limited-liability constraint of a regulator.
On the other hand, under the decentralized laissez-faire economy, our model suggests excessivecompensation can reduce social welfare by squeezing production. To achieve the efficient level ofproduction, corporate sanction, contingent on the level of a worker’s compensation, is mandatory.
As opposed to the existing literature, our model even rationalizes the government’s subsidy andbailout in order to fix the shrink of production owing to excessive compensation.

1

Faculty of Law, Kyoto University, Yoshidahonmachi, Sakyo Ward, Kyoto, 606-8314, Japan. Email:inatani.tatsuhiko.3w@kyoto-u.ac.jp.
2
College of Business and Economics, Australian National University, 26C Kingsley Street Acton, ACT, 2601,
Australia. Email:kentaro.asai@anu.edu.au.

1. Introduction
Law scholars and financiers have tackled corporate crime matters in many ways (See e.g.
Edgerton (1927), Muller (1957), Elkins (1976), Orland (1980), Coffee (1981), Fisse (1983), Bucy
(1991), Fisse & Braithwaite (1993)). One of the most promising ways is economic analysis that
seems to influence corporate crime policy significantly in the U.S. (See e.g. Arlen (1994), Arlen& Kraakman (1997), Arlen (2012)) and other countries (See Arlen (2020) and Arlen & Buell(forthcoming)). Under the unignorable influence of the canonical work of Becker (1968), most oflaw and economics literatures have chosen monetary sanction as the first choice of formal sanction
to be imposed on rogue employee for deterrence. This choice seems very persuasive and even
irrefutable, if we analyze static and fragmented world.
However, many law literatures of punishment have focused not only on static situation but on
dynamic situation caused by the very punishment would be imposed on wrongdoers. They
demonstrate the prospective impact of punishment in multiple ways. For example, Beccaria (1764),
the god father of modern criminal law, demonstrated the future impact of public exposure of forcedlabor in his famous “On Crime and Punishment.” Rousseau (1755) who illustrated the function ofstate power as a clue to solve coordination problem in dynamic game situation, might overlap his
interest with a recent research of the “expressive function” of criminal punishment which focuseson the power of punishment that changes the behavior of potential perpetrators (McAdams, 2015).
We may add Hegelian theory of punishment to the list which puts importance on cognitive
assurance function of criminal punishment through rebuilding the confidence of legal stability of
citizens who are shocked by crime and start to suspect the effectiveness of law (See Hegel (1820)
and Jakobs (1997)).

In addition to their dynamic view, it is worth demonstrating that in modern society people livein the integrated world where their lives in corporation intrinsically connect to their lives in othersocial domains. It means that when we treat misconduct in corporation, it is better to take accountin the influence of sanctions upon individuals and corporations relating to the misconduct inbroader social context, because in our society most people earn their living expenses from
corporations or other forms of organization. Therefor it seems us that there is a gap between
previous economic analysis of punishment and legal literature of punishment. We wonder if many
economic analyses may fail to take account in important feature of criminal punishment, that is
criminal punishment works in dynamic and integrated world that will be or was influenced by thevery punishment itself. 3 As we will show, this gap leads to underestimate the efficiency of
imprisonment and stigmatizing effect of punishment and ultimately to understand the severity ofcurrent imprisonment punishment, which works in free and open society where many people earn
their life through time-based income, difficultly. 4 In this article we take account in this interconstructive relationship between punishment and the dynamic situation surrounding thepunishment through dynamic economic analysis of corporate punishment. This work will bridge
the current gap described above and deepen the understanding of punishment, which ultimately
leads better understanding of imprisonment in general.
Among various types of misconduct, we focus on white-collar crimes by executive workers,
as the initial step toward the dynamic economic analysis of punishment. Because executive
workers earn relatively high compensation, the suspension of their future business throughFrancesco Guala, who defines institutions as “rules-in-equilibrium” in dynamic games, demonstrates a constructive
character of legal rules (Guala, 2016).
4
As Foucault illustrated, modern punishment measures like imprisonment in correction facility, had been formed inemerging modern society where “good” labor force became keenly demanded through industrialization (Foucault,
1977). Although prison comes to serve for different function of incapacitation after the “late modernity” (Garland,2001) .
3

imprisonment or license removal is particularly relevant for deterring their crimes. Motivated bythis conjecture, we incorporate the suspension of future economic activity into the model ofcorporate misconduct by Arlen & Kraakman (1997) as the primary method of criminal punishment
on a wrongdoer. In our model, a worker has the opportunity of committing a wrong every period.
A worker uses a threshold (reservation value) strategy to determine whether to commit a wrong orwork prudently. A regulator monitors a worker stochastically, and deprives him of future economic
activity when his wrongdoing is detected. Depriving a wrongdoer of his opportunity to work in the
future relaxes the limited-liability constraint for a regulator and enhances the capacity ofpunishment, as it allows a regulator to penalize a wrongdoer effectively even if a wrongdoer has
had little wealth or consumed all the existing wealth before being detected. Then, the reservation
value for committing a wrong is, ceteris paribus, greater in the presence of suspension than the one
characterized by Arlen & Kraakman (1997). As the wealth to be lost by a wrongdoer throughpunishment depends on his income stream in the future, the model becomes dynamic by nature.
Although our dynamic model becomes intrinsically complex, it gives us useful implications undercertain special, but reasonably realistic cases.
We derive four major outcomes from our model. First, we find intensifying suspension andraising a worker’s income stream unambiguously improve social welfare under the centralized
economy or economy with corporate sanction. Both strengthen the effect of monitoring by
imposing severer sanction upon the detection of wrongdoing. Second, under cheap monitoring cost,
there is substitutional relationship between the efficient level of monitoring and the size of sanction.
In particular, the efficient level of monitoring decreases in the level of a worker’s income stream
and the intensity of suspension. On the same ground, the efficient level of monitoring decreases ina firm’s age, if a worker’s compensation grows or suspension intensifies over time. Third, underthe decentralized laissez-faire economy, excessive compensation can reduce social welfare bysqueezing production. Under the unregulated economy, a firm’s choice of production decreases ina worker’s compensation, which is a part of production cost incurred by a firm. This result is
contrastive to the favourable impact of a worker’s compensation under the regulated economy.
Last, the efficient level of corporate sanction can be both positive and negative, depending on thelevel of a worker’s compensation. If a worker’s compensation is sufficiently large, the efficientlevel of corporate sanction becomes negative. What is more, the size of optimal subsidy canincrease in the level of a worker’s compensation, because the optimal frequency of detecting awrong can decrease in a worker’s compensation, which needs to be compensated to sustain the
expected level of subsidy.
Our results imply a key deterrent to corporate misconduct is a worker’s income stream,
affected by his prospective compensation. On the one hand, raising income stream improves social
welfare unambiguously under the regulated economy. On the other hand, excessive compensation
can aggravate efficiency under the unregulated economy. To achieve an efficient outcome under
the decentralized economy, corporate sanction is essential for inducing a firm to internalize thesocial harm of business activity attributed to its worker’s wrongdoing. The size of sanction depends
on the level of a worker’s compensation. In fact, it can be even negative if a worker’s compensation
is sufficiently large. Thus, if a regulator aims to achieve social optimum by raising a worker’s
compensation as much as possible, there is possibility that a regulator subsidizes a firm when awrongdoing is detected, because a firm pays too much cost for its production without subsidy. This
result is contrastive to the proposal of penalizing a firm upon the detection of wrongdoing by Arlen& Kraakman (1997).

Moreover, our analysis suggests the efficient level of monitoring, or probability of detecting
a wrong, decreases in a worker’s income stream and the intensity of suspension, at least whenmonitoring cost is relatively cheap. Although monitoring cost can be high in the presence of severe
information asymmetry between a firm and a regulator, it can be small under the modern system
of internal governance and the scheme designed to encourage self-reporting a wrong. For example,
public companies have enhanced financial disclosure since the Sarbanes–Oxley (SOX) Act of
2002, while the Department of Justice (DOJ) has encouraged whistle-blowing and self-reporting
through Deferred Prosecution Agreements (DPA) and leniency program. This result suggests
excessive monitoring is unnecessary in the presence of high compensation under the modern
system of internal governance and the incentive scheme that encourages self-reporting. On thesame ground, this result motivates the life-cycle theory of efficient monitoring: a younger firmshould be monitored more frequently than an elder firm if a firm’s compensation grows over time.
Our work first contributes to the economic analysis of law enforcement by explicitly
incorporating the suspension of future economic activity into the theory of deterrence. The existing
economic theory of deterrence builds on idea that monitoring, or the probability of detecting awrong, and the severity of sanction jointly deter a crime (Garoupa, 2002). Becker (1968) argues
maximizing fine is the optimal way of deterring a crime, considering it minimizes the need forcostly monitoring whereas it is a costless transfer for a society. However, maximizing fine is not
so effective when a wrongdoer has limited wealth, suggesting the difficulty of efficient deterrence
through monetary sanction. In response to this problem, some of the following studies emphasize
the importance of observing an idiosyncratic characteristic of an individual and a wrong. Theyshow this limited-liability constraint is unlikely to bind at least for certain individuals and crimes.
For example, Shavell (1987) argues expensive fines are often unnecessary for a petty crimecommitted by a poor individual, because a private benefit from wrongdoing is likely to be large
relative to a harm imposed on a society5. In another example, Bebchuk & Kaplow (1993) find the
optimal fines should be less than maximal for individuals who are less difficult to apprehend.
Moreover, others argue substituting fines with monitoring is not as costly as thought by Becker(1968). For example, Kaplow & Shavell (1994) find a regulator can raise monitoring intensity
without spending resources by pre-committing to offer less severe penalties to those who selfreport harm-producing actions. They suggest raising the probability of deterring a wrong througha leniency program can reduce fines without sacrificing deterrent effect. Unlike these studies, ourwork rather questions the presence of limited-liability constraint itself by reconsidering thedefinition of an individual’s “wealth.” As admitted by Becker himself, the amount of time
available to an individual multiplied by his wage is a significant component of his “life-time wealth”(Becker, 1965). In this spirit, our work models the life-time wealth of an individual who faces theopportunity of wrongdoing and the risk of being detected and suspended in order to characterize
the deterrent effect of removing one’s future life-time through suspension. This feature is distinct
from the earlier literature of non-monetary sanctions (See e.g. Block & Lind (1975), Polinsky &Shavell (1999)).
Moreover, our policy implication contributes to the ongoing discussion of executive
compensation regulation. Specifically, our results suggest lowering the level of executive
compensation weakens the deterrent effect of suspension, which is contrastive to the recent
regulatory trend of restricting executive compensation level in response to the Global Financial
Crisis (GFC). Indeed, the Dodd-Frank Act (DFA) of 2010 requires the Securities and Exchange
5

Researchers in corporate law and finance rather attempt to rationalize the limited liability of a corporate controller(e.g., an owner-manager) by arguing it raises capital supply in financial market, precludes the adverse selection ofpoor investors, and reveals valuable information to public. See Easterbrook and Fischel (1985), Winton (1993), andAsai (2020), for example.

Commission (SEC) to implement rules mandating U.S. companies to adopt clawback policies,
whereas the Capital Requirements Directive (CRD IV) caps the bonuses of executive bankers in
E.U. Our work complements the existing research by assessing the effect of compensation levelon business conduct, rather than the effect of pay structure, which has been the main focus of therecent work on executive compensation (See e.g. Fahlenbrach & Stulz (2011), DeYoung et al.
(2013), Brandão Marques et al. (2014), Asai (2016), Albuquerque et al. (2019)).

2. ModelWe make a model of corporate wrongdoing in the spirit of Arlen & Kraakman (1997). As in
Arlen & Kraakman (1997), a risk neutral firm hires risk neutral agents to produce a product. Each
employee is penniless, producing one unit of the product per period. Total firm production inperiod 𝑡, which is equivalent to total employment per period, is given by 𝑞𝑡 (𝑞𝑡 > 0 ). 6 The
revenue of the firm’s production is given by 𝑉(𝑞𝑡 ). We assume 𝑉 satisfies Inada conditions.
Although it is easiest to interpret 𝑞𝑡 as the number of employees, 𝑞𝑡 can be considered as the ``size”
of the firm (e.g., the level of investment or external capital) under the condition that the number of
employees is proportional to the firm’s size.
Each firm incurs the cost from production every period which has a monetary value of 𝑘 (𝑘 ≥0). Departing from Arlen & Kraakman (1997), we assume each firm pays base salary, 𝑤𝑡 , to each
employee (𝑤𝑡 ≥ 0). The salary is exogenous and immediately consumable for the fraction of 1 −6

Polinsky & Shavell (1993) also analyze corporate misconduct while endogenizing a firm’s output level.

𝛼 (0 ≤ 𝛼 < 1); 1 − 𝛼 of 𝑤𝑡 cannot be transferred from an employee to a third party after theemployee receives it.
Each employee has the opportunity to commit a wrong every period. The cost to society ofeach wrong is 𝐻. The benefit to an employee of wrongdoing is given by 𝑏, which varies acrossemployees. It is independent and identically distributed over time. Neither the regulator nor thefirm knows any individual’s 𝑏 . Instead, the regulator and firm know the probability density
function and the cumulative distribution function of 𝑏 , which is given by 𝑟(𝑏) and 𝑅(𝑏) ,respectively. The firm also receives a surplus, 𝐵, from wrongdoing.
Wrongdoing is socially optimal if the net benefit of wrongdoing exceeds the social cost of thewrong:
𝑏 + 𝐵 > 𝐻.
On the other hand, an employee commits a wrong when his personal benefit exceeds the cost ofwrongdoing.
In the absence of non-negative wealth constraint, the planner can induce employees to refrainfrom suboptimal wrongdoing by imposing the sanction equal to, 𝐻 − 𝐵, divided by the probabilityof detection. This sanction, however, is unlikely to be paid by each employee in the presence oflimited liability, because he does not have sufficient wealth.
To deter wrongdoing, the planner has to rely on non-monetary sanctions, such as
imprisonment and suspension. For the ease of exposition, we discuss the model in the context of
imprisonment, but such imprisonment can be generalizable to any type of suspension. As
suggested by the previous research, such non-monetary sanction can increase the amount ofpenalties by removing the opportunity of working in the future.

To characterize this effect formally, we model the life-time wealth of a worker who faces theopportunity of wrongdoing and the risk of being detected and suspended. Each employee is hiredby the firm each period until terminal period 𝑇 unless he is in “prison.”7 In period 𝑡, each employee
knows the probability of being detected at the end of the period, 𝑝(𝑀𝑡′ ), where 𝑀𝑡′ is the planner’s
monitoring for ∀𝑡 ′ ≥ 𝑡 ( 𝑀𝑡′ > 0, ∀𝑡 ′ ≥ 𝑡) . We consider that 𝛼𝑤𝑡 is confiscated when his
wrongdoing is detected, because it is transferrable. If he does not commit a wrong, his value is thediscounted value of being out of prison in 𝑡 + 1 plus the current salary 𝑤𝑡 . Then he commits awrong if and only if:𝑏 − 𝑝(𝑀𝑡 )𝛼𝑤𝑡 + 𝛽 ((1 − 𝑝(𝑀𝑡 ))𝑊𝑡+1 + 𝑝(𝑀𝑡 )𝑈𝑡+1 ) ≥ 𝛽𝑊𝑡+1 , (1)where 𝛽 is the discount factor (0 ≤ 𝛽 < 1). Therefore, his value of being out of prison in 𝑡, 𝑊𝑡 , is∞𝑊𝑡 = ∫(𝑏 − 𝑝(𝑀𝑡 )(𝛼𝑤𝑡 + 𝛽(𝑊𝑡+1 − 𝑈𝑡+1 ) ))𝑟(𝑏)𝑑𝑏𝑝(𝑀𝑡 )(𝛼𝑤𝑡 +𝛽(𝑊𝑡+1 −𝑈𝑡+1 ))+𝑤𝑡 + 𝛽𝑊𝑡+1 . (2)On the other hand, his value of being in prison at the beginning of 𝑡 is the weighted average of thevalue when he is released from prison and the discounted value of 𝑈𝑡+1 .
𝑈𝑡 = 𝜆𝑡 𝑊𝑡 + (1 − 𝜆𝑡 )𝛽𝑈𝑡+1 , (3)where 𝜆𝑡 is the probability of being released from prison. Note that the probability of being
released from prison, 𝜆𝑡 , captures the intensity of imprisonment. If it is zero, that is, if an employee
cannot escape from prison, his value of being in prison is zero. In this case, his cost of committing
a wrong is maximized. If it is one, that is, if he can always escape from prison, his value of being

7

Here, we refer to any type of confinement, not necessarily imprisonment.

in prison is equal to the value of being out of prison. Then his cost of committing a wrong is
minimized and equal to the one in the absence of imprisonment.8 Given the value of an employee
after the terminal period {𝑊𝑇+1 , 𝑈𝑇+1 }, we can recursively solve {𝑊𝑡 ′ , 𝑈𝑡′ } for ∀𝑡 ′ ≥ 𝑡 as afunction of variables {𝑀𝑡 ′′ , 𝜆𝑡 ′′ , 𝑤𝑡′′ } for ∀𝑡 ′′ ≥ 𝑡′.
The social welfare induced by the firm is the sum of current and discounted future surplus.
Then, it is characterized by:𝑇

𝑆 = ∑ 𝛽𝑡
𝑡=0

−𝑞𝑡 [
{

∞

𝑉(𝑞𝑡 )
𝑘 + 𝑐𝑀𝑡+∫(𝐻 − 𝑏 − 𝐵)𝑟(𝑏)𝑑𝑏𝑝(𝑀𝑡 )(𝛼𝑤𝑡 +𝛽(𝑊𝑡+1 −𝑈𝑡+1 )),]}̅ , 𝑈𝑇+1 = 𝑈
̅, (4)
subject to 𝑊𝑇+1 = 𝑊
where 𝑐𝑀𝑡 is the monitoring cost per employee incurred by the society (𝑐 ≥ 0). For the rest of thepaper, we denote equilibrium outcome by superscript ∗.

3. Social planner’s problem
We start from considering the equilibrium under which the social planner determines thefirm’s employment and the level of monitoring. Then, the equilibrium is defined by:̅ , 𝑈𝑇+1 = 𝑈̅.
𝑆 ∗ = max 𝑆 subject to 𝑊𝑇+1 = 𝑊{𝑞𝑡 ,𝑀𝑡 }8

In this paper, we consider the cost of imprisonment is zero and the probability of being released from prison isexogenous.

To clarify the link to Arlen & Kraakman (1997), we start from solving the social planner’s
problem when there is no imprisonment, that is, 𝜆𝑡 = 1, ∀0 ≤ 𝑡 ≤ 𝑇. Then, 𝑊𝑡+1 = 𝑈𝑡+1 , ∀0 ≤𝑡 ≤ 𝑇. The first order conditions with respect to {𝑞𝑡 , 𝑀𝑡 } are:𝑉 ′ (𝑞𝑡 ) = 𝑘 + 𝑐𝑀𝑡 + (𝐻 − 𝐸[𝑏|𝑏 ≥ 𝑏̂𝑡 ] − 𝐵) (1 − 𝑅(𝑏̂𝑡 )), (5)′𝑝⏟ (𝑀𝑡 )𝛼𝑤𝑡 𝑟(𝑏̂𝑡 ) 𝑎̂𝑡 = 𝑐, (6)dec. in wrongdoers in t

where 𝑎̂𝑡 = 𝐻 − 𝑝(𝑀𝑡 )𝛼𝑤𝑡 − 𝐵, 𝑏̂𝑡 = 𝑝(𝑀𝑡 )𝛼𝑤𝑡 . 𝑎̂𝑡 represents the social loss of the marginalwrongdoer. 𝑏̂𝑡 represents the reservation value for wrongdoing. The first condition suggests that
employment level is optimal when the marginal social benefit of additional employment, 𝑉′(𝑞𝑡 ),equals the marginal social cost of employment. The second condition means that monitoring levelis optimal when the marginal social cost of monitoring per worker, 𝑐, equals the marginal social
benefit of monitoring per worker. These conditions suggest the dynamics of optimal {𝑞𝑡 , 𝑀𝑡 } are
driven by the salary of an employee 𝑤𝑡 . If 𝑤𝑡 = 𝑤 where 𝑤 is some constant, they are equivalent
to those in the static version proposed by Arlen & Kraakman (1997).
Unlike the static version, the wealth of the wrongdoer that he loses when his wrongdoing is
detected includes the discounted net value of being out of prison, 𝛽(𝑊𝑡+1 − 𝑈𝑡+1 ) .
Correspondingly, the social loss of the marginal wrongdoer is represented by𝑎̃𝑡 = 𝐻 − 𝑝(𝑀𝑡 )(𝛼𝑤𝑡 + 𝛽(𝑊𝑡+1 − 𝑈𝑡+1 )) − 𝐵.
Also, the reservation value for wrongdoing is represented by𝑏̃𝑡 = 𝑝(𝑀𝑡 )(𝛼𝑤𝑡 + 𝛽(𝑊𝑡+1 − 𝑈𝑡+1 )).
As a result, the wrongdoer’s reservation value is larger than the one in the static version.

Whereas the optimal monitoring level is hard to characterize in the dynamic model, theoptimal employment is characterized in the similar manner as in the static version. Specifically, itsatisfies:
𝑉 ′ (𝑞𝑡 ) = 𝑘 + 𝑐𝑀𝑡∗ + (𝐻 − 𝐸[𝑏|𝑏 ≥ 𝑏̃𝑡∗ ] − 𝐵) (1 − 𝑅(𝑏̃𝑡∗ )), (7)where 𝑏̃𝑡∗ is 𝑏̃𝑡 evaluated at the optimal monitoring level 𝑀𝑡∗ . Then, we claim the following:
Proposition 1: Under the social planner’s problem, 𝑞𝑡∗ satisfies equation (7).
Proof: Obvious.
For the following part, we describe special cases that allow us to acquire analytical
implications.
3-1. Social planner’s problem under stationary model
We first consider a stationary version in which all the parameters and control variables aretime-invariant while 𝑇 = ∞. Under this condition, the value of an employee becomes also timeinvariant. Specifically, we solve the following value function.

𝑆∗𝑡= max ∑∞
𝑡=0 𝛽 {
{𝑞,𝑀}
−𝑞 [

𝑉(𝑞)
𝑘 + 𝑐𝑀}.
∞+ ∫𝑝(𝑀)(𝛼𝑤+𝛽(𝑊−𝑈))(𝐻 − 𝑏 − 𝐵)𝑟(𝑏)𝑑𝑏]

The first order conditions with respect to {𝑞 , 𝑀 } are:𝑉 ′ (𝑞) = 𝑘 + 𝑐𝑀 + (𝐻 − 𝐸[𝑏|𝑏 ≥ 𝑏̃] − 𝐵) (1 − 𝑅(𝑏̃)), (8)(𝑝′(𝑀)(𝛼𝑤+ 𝛽Γ𝑊) + 𝑝(𝑀)𝛽Γ(𝜕𝑊/𝜕𝑀))𝑟(𝑏̃) 𝑎̃ = 𝑐, (9)⏟dec. in wrongdoerswhere𝑎̃ = 𝐻 − 𝑝(𝑀)(𝛼𝑤 + 𝛽Γ𝑊) − 𝐵 , 𝑏̃ = 𝑝(𝑀)(𝛼𝑤 + 𝛽Γ𝑊) , and Γ = (1 − 𝜆)(1 − 𝛽)/(1 − (1 − 𝜆)𝛽). In this version, the wealth of the wrongdoer that he loses when his wrongdoing
is detected includes the discounted net value of being out of prison, 𝛽Γ𝑊.
As indicated above, the discounted net value of being out of prison is simplified to a linear
function of the value of being out of prison 𝑊 under the stationary model. The coefficient Γ
captures the intensity of suspension. If the probability of being released from a prison is 1, Γ = 0
as there is no penalty of being detected. However, if the probability of being detected is 0, Γ = 1
as a wrongdoer completely loses the opportunity of future economic activity, suggesting he would
lose the entire value of being out of prison 𝑊.
We now investigate the welfare implication of this special case. In particular, we assess theeffects of parameters on social welfare. We claim:
Proposition 2: Under the stationary social planner’s problem, {𝑞 ∗ , 𝑀∗ } satisfies equations (8) and(9) evaluated at {𝑞, 𝑀} = {𝑞 ∗ , 𝑀∗ }. Moreover, 𝑑𝑆 ∗ /𝑑𝜆 ≤ 0, 𝑑𝑆 ∗ /𝑑𝑤 ≥ 0.
Proof: See Appendix.
Raising the salary of an employee and lowering the probability of releasing a prisoner is welfareenhancing. By raising the wealth that an employee loses when his wrongdoing is detected, theplanner can deter wrongdoing with less resources.
The policy implication from this result is perhaps surprising. Because 𝑤 raises social welfare
unambiguously, the planner should raise the salary of an employee as much as possible. Despite
the criticism against the relatively high salary of a potential wrongdoer, our analysis rather
rationalizes it as an efficient outcome.

3-2. Social planner’s problem under zero monitoring cost
We reconsider the original dynamic model, but we now assume the cost of monitoring is zero(𝑐 = 0). We also assume the economy stays at the stationary equilibrium since 𝑇 + 1. Then, suchcondition can be described by setting 𝑊𝑇+1 = 𝑊 ∗ and 𝑈𝑇+1 = 𝑈 ∗ , where 𝑊 ∗ and 𝑈 ∗ are 𝑊 and𝑈 evaluated at some equilibrium of the social planner’s problem under the stationary version. We
denote the stationary level of wage and releasing probability by 𝑤 and 𝜆, respectively. Trivially,
if every 𝑤𝑡 and 𝜆𝑡 is equal to 𝑤 and 𝜆 , respectively, the model becomes equivalent to thestationary model with 𝑐 = 0.
When monitoring is costless, the monitoring level is set so that the net social harm, 𝑎̃𝑡 ,becomes zero for every 𝑡. This means the planner raises monitoring level until the social loss ofthe marginal wrongdoer becomes zero. Indeed, if monitoring exceeded that level, the marginalwrongdoer would raise social welfare by wrongdoing and the planner could raise social welfare
by reducing monitoring level to attract more wrongdoers. On the other hand, if monitoring fell
below that level, the marginal wrongdoer would reduce social welfare by wrongdoing and theplanner could raise social welfare by strengthening monitoring level to reduce wrongdoers without
incurring cost. It therefore suggests:
𝑎̃𝑡 = 𝐻 − 𝑝(𝑀𝑡 )(𝛼𝑤𝑡 + 𝛽(𝑊𝑡+1 − 𝑈𝑡+1 )) − 𝐵 = 0. (10)Equation (10) suggests the reservation value for wrongdoing, 𝑏̃𝑡 , is 𝐻 − 𝐵. Then, the first ordercondition with respect to {𝑞𝑡 } is:
𝑉 ′ (𝑞𝑡 ) = 𝑘 + (𝐻 − 𝐸[𝑏|𝑏 ≥ 𝐻 − 𝐵] − 𝐵)(1 − 𝑅(𝐻 − 𝐵)). (11)This result suggests the optimal firm size is constant to 𝑡. Hence, 𝑞𝑡∗ = 𝑞 ∗ for all 𝑡.

We now investigate the dynamics of monitoring level for this special case. In particular,
we assess the effect of monotone trend of a parameter on the optimal level of monitoring. Because
the monotone trend of a parameter induces the monotone trend of the wealth that an employee
loses when his wrongdoing is detected, it induces the monotone trend of optimal monitoring level
as the planner substitutes the wealth that an employee loses and the level of monitoring to achieve
efficient deterrence against wrongdoing. Specifically, we claim the following.
Proposition 3: Under the social planner’s problem under zero monitoring cost, {𝑞𝑡∗ , 𝑀𝑡∗ } satisfies
equations (10) and (11) evaluated at {𝑞𝑡 , 𝑀𝑡 } = {𝑞𝑡∗ , 𝑀𝑡∗ }. Then, 𝑞𝑡∗ is constant and invariant tosalary and releasing probability at any 𝑡. Also, if 𝑤𝑡 weakly increases (decreases) in 𝑡 while 𝜆𝑡
weakly decreases (increases) in 𝑡, 𝑞𝑡∗ = 𝑞 ∗ and 𝑀𝑡∗ weakly decreases (increases) in 𝑡. Under thestationary model, 𝑑𝑞 ∗ /𝑑𝜆 = 0, 𝑑𝑞 ∗ /𝑑𝑤 = 0, 𝑑𝑀∗ /𝑑𝜆 ≥ 0, 𝑑𝑀∗ /𝑑𝑤 ≤ 0.
Proof: The constancy of 𝑞𝑡∗ and its independence from salaries and releasing probability is obvious
from equation (11). See Appendix for the rest.
Overall, this result indicates substitutional relationship between optimal monitoring and nonmonetary sanction. If salary rises or releasing probability decreases, the optimal level of nonmonetary sanction rises. Consequently, there is less monitoring required to achieve the efficient
outcome.
This result also suggests as compensation grows (declines) while releasing probability
declines (grows), the optimal level of monitoring declines (rises). It also suggests the optimal
monitoring level depends on the life cycle of a firm. A regulator wants to raise monitoring intensity
for a younger firm if a firm’s compensation grows while releasing probability decreases by firmage, whereas the opposite should be valid if a firm’s compensation falls while releasing probability
increases by firm age.

4. Decentralized economy
In this section, we analyze the economy in which the firm’s shareholder determines the firm’ssize, 𝑞𝑡 . Let 𝑀𝑡∗ be the optimal level of monitoring set by the social planner as in the planner’s
problem. Then, the shareholder maximizes her value by solving:𝑇max ∑ 𝛽 𝑡
{𝑞𝑡 }

𝑡=0

−𝑞𝑡 [+ ∫{∞𝑉(𝑞𝑡 )
𝑘 + 𝑤𝑡,(−𝐵)𝑟(𝑏)𝑑𝑏]∗ −𝑈 ∗ ))𝑝(𝑀𝑡∗ )(𝛼𝑤𝑡 +𝛽(𝑊𝑡+1
𝑡+1}

where {𝑊𝑡∗ , 𝑈𝑡∗ } is {𝑊𝑡 , 𝑈𝑡 } evaluated at 𝑀𝑡 = 𝑀𝑡∗ . The first order condition with respect to 𝑞𝑡 is:
𝑉 ′ (𝑞𝑡 ) = 𝑘 + 𝑤𝑡 + (−𝐵) (1 − 𝑅(𝑏̃𝑡∗ )), (12)where 𝑏̃𝑡∗ is 𝑏̃𝑡 evaluated at 𝑀𝑡 = 𝑀𝑡∗ . Then, we claim the following:
Proposition 4: Under the decentralized economy, 𝑞𝑡∗ satisfies equation (12).
Proof: Obvious.
Unlike the social planner’s problem, the firm’s marginal cost of hiring an employee increases
in the salary of an employee in the decentralized economy. Moreover, it ignores the harm incurredby the society and the benefit received by an employee from wrongdoing. Further, it does notaccount for the monitoring cost incurred by the society.
4-1. Decentralized economy under special cases

When the shareholder’s surplus from wrongdoing is zero (𝐵 = 0), the shareholder’s marginal
cost of hiring only depends on the salary of an employee 𝑤𝑡 . As a result, the firm size chosen by
the shareholder, 𝑞𝑡∗ , does not interact with the monitoring level chosen by the planner, 𝑀𝑡∗ .
In addition, when monitoring cost is zero (𝑐 = 0), the planner sets 𝑀𝑡∗ such that 𝑎̃𝑡∗ = 0 and𝑏̃𝑡∗ = 𝐻 − 𝐵 as discussed in the previous section. Because the expected benefit of the shareholder
from wrongdoing is now fixed to 𝐵(1 − 𝑅(𝐻 − 𝐵)), the shareholder’s marginal cost of hiring only
depends on the salary of an employee 𝑤𝑡 and some fixed cost associated with firm size 𝑘. Again,
the firm size chosen by the shareholder, 𝑞𝑡∗ , does not interact with the monitoring level chosen by
the planner, 𝑀𝑡∗ .
These two observations allow us to claim the following.
Proposition 5: Suppose 𝐵 = 0 or 𝑐 = 0 under the decentralized economy. 𝑑𝑞𝑡∗ /𝑑𝜆𝑡 = 0, 𝑑𝑞𝑡∗ /∗∗𝑑𝑤𝑡 < 0, 𝑑𝑞𝑡′
/𝑑𝜆𝑡 = 0, 𝑑𝑞𝑡′
/𝑑𝑤𝑡 = 0, ∀𝑡 ′ ≠ 𝑡. Moreover, 𝑆 ∗ → 0, 𝑞𝑡∗ → 0, as 𝑤𝑡 → ∞, ∀𝑡 ≥ 0.

Similarly, under the stationary model, 𝑑𝑞 ∗ /𝑑𝜆 = 0, 𝑑𝑞 ∗ /𝑑𝑤 < 0, and 𝑆 ∗ → 0, 𝑞 ∗ → 0, as 𝑤 →∞.
Proof: Obvious from equation (12) regarding the result about 𝑞𝑡∗ . Also, due to Inada condition,𝑞𝑡∗ → 0 as 𝑤𝑡 → ∞ and the right-hand-side diverges to ∞.
This result suggests, under certain conditions, as compensation grows, the firm size declines
whereas the welfare of the economy starts to decline at some point. In the limit case under which
the salary of an employee is infinitely large, the welfare of the economy converges to zero, whichis the lower bound of the welfare of the economy under the planner’s problem. Thus, excessive
salary can reduce social welfare under this setup, which is contrastive to the implication from thesocial planner’s problem.

5. Decentralized economy with corporate sanction
Keeping the setup of the decentralized economy, we now allow the planner to introduce
corporate sanction, 𝐹𝑡 , which is the transfer from the firm to the planner when corporate
wrongdoing is detected. Let 𝑀𝑡∗ be the optimal level of monitoring set by the social planner as in
the planner’s problem. Then, in the presence of this sanction, the shareholder’s problem is:𝑇

max ∑ 𝛽 𝑡
{𝑞𝑡 }

𝑡=0

−𝑞𝑡 [+ ∫{∞𝑉(𝑞𝑡 )
𝑘 + 𝑤𝑡(𝑝(𝑀𝑡∗ )𝐹𝑡 − 𝐵)𝑟(𝑏)𝑑𝑏]∗ −𝑈 ∗ ))𝑝(𝑀𝑡∗ )(𝛼𝑤𝑡 +𝛽(𝑊𝑡+1
𝑡+1
}

.

The first order condition with respect to 𝑞𝑡 is:
𝑉 ′ (𝑞𝑡 ) = 𝑘 + 𝑤𝑡 + (𝐸[𝑝(𝑀𝑡∗ )𝐹𝑡 |𝑏 ≥ 𝑏̃𝑡∗ ] − 𝐵) (1 − 𝑅(𝑏̃𝑡∗ )), (13)where 𝑏̃𝑡∗ is 𝑏̃𝑡 evaluated at 𝑀𝑡 = 𝑀𝑡∗ . Considering the first order condition with respect to {𝑞𝑡 } forthe planner’s problem (see equation (7)),9 the optimal corporate sanction, 𝐹𝑡∗ , is:𝐹𝑡∗ = (𝐻 − 𝑏)/𝑝(𝑀𝑡∗ ) + (𝑐𝑀𝑡∗ − 𝑤𝑡 )/ (𝑝(𝑀𝑡∗ ) (1 − 𝑅(𝑏̃𝑡∗ ))). (14)Alternatively, if the planner does not observe the benefit of the employee who commits
wrongdoing, the planner can set:

9

The planner achieves the social optimum by setting 𝐹𝑡 such that
𝐸[𝑝(𝑀𝑡∗ )𝐹𝑡 |𝑏 ≥ 𝑏̃𝑡∗ ] − 𝐵 = (𝑐𝑀𝑡∗ − 𝑤𝑡 )/ (1 − 𝑅(𝑏̃𝑡∗ )) + 𝐻 − 𝐸[𝑏|𝑏 ≥ 𝑏̃𝑡∗ ] − 𝐵.

𝐹𝑡∗ = (𝐻 − 𝐸[𝑏|𝑏 ≥ 𝑏̃𝑡∗ ])/𝑝(𝑀𝑡∗ ) + (𝑐𝑀𝑡∗ − 𝑤𝑡 )/ (𝑝(𝑀𝑡∗ ) (1 − 𝑅(𝑏̃𝑡∗ ))). (15)
In summary, we claim the following.
Proposition 6: Under the decentralized economy, 𝑞𝑡∗ satisfies equation (13). At 𝐹𝑡 = 𝐹𝑡∗ set inaccordance with equation (14) or (15), the planner achieves the optimal level of firm size andmonitoring under the social planner’s problem.
Proof: Obvious from the above argument.
This result suggests corporate sanction is required even if a wrongdoer is optimally monitored.
The major difference between this model and Arlen & Kraakman (1997) is the consideration of an
employee’s salary. If everything else equal, an employee’s salary is negatively associated with the
optimal level of corporate sanction. Then, the policy implication from this result is perhaps
surprising. To see how, let us consider the stationary equilibrium. Because the salary of an
employee raises social welfare unambiguously, a planner should raise the salary of an employee
as much as possible. Moreover, because the optimal level of corporate sanction decreases in thesalary of an employee ceteris paribus, the optimal level of corporate sanction could be evennegative. Thus, Proposition 6 suggests a firm might be subsidized when wrongdoing is detected.
Despite the criticism against the bail out of a failing firm owing to corporate misconduct and thehigh salary of its employees, our analysis provides the possibility of rationalizing bothobservations as an efficient outcome.
5-1. Decentralized economy with corporate sanction under special cases
We can formally verify this conjecture by focusing on the stationary case in which monitoring
cost is zero. In this case, the reservation value for wrongdoing is fixed such that 𝑏̃ ∗ = 𝐻 − 𝐵, so

𝑀∗ decreases in 𝑤 as the planner substitutes monitoring intensity with the size of wealth lost by awrongdoer upon detection. When the salary is sufficiently large, the firm is subsidized whenwrongdoing is detected. Then, the size of the subsidy increases as monitoring intensity decreases.
Proposition 7: Suppose the stationary model under 𝑐 = 0 . If 𝑤/(1 − 𝑅(𝐻 − 𝐵)) ≥ 𝐻 −𝐸[𝑏|𝑏 ≥ 𝐻 − 𝐵], 𝐹 ∗ ≤ 0 and 𝐹 ∗ decreases in 𝑤. If 𝑤/(1 − 𝑅(𝐻 − 𝐵)) < 𝐻 − 𝐸[𝑏|𝑏 ≥ 𝐻 − 𝐵],
𝐹 ∗ > 0.
Proof: See Appendix.
We, however, caution that this result does not rule out the possibility of corporate sanction. In
particular, if the salary is sufficiently small, the firm is penalized when wrongdoing is detected.

6. Policy Implication
Our results imply a key deterrent to corporate misconduct is a worker’s income stream, affectedby his prospective compensation. Under the regulated economy, restricting compensation level
weakens the deterrent effect of suspension on corporate misconduct. This result is contrastive tothe current trend of executive compensation regulation such as DFA in the U.S. and CRD-IV in
E.U. Under the decentralized economy, our results imply corporate sanction is essential for
inducing a firm to internalize the social harm of business activity attributed to its worker’s
wrongdoing. In fact, it can be even negative if a worker’s compensation is sufficiently large. Thus,
if a regulator aims to achieve social optimum by raising a worker’s compensation as much as
possible, there is possibility that a regulator subsidizes a firm when a wrongdoing is detected,
because a firm pays too much cost for its production without subsidy. This result is contrastive tothe proposal of penalizing a firm upon the detection of wrongdoing by Arlen & Kraakman (1997).

Moreover, our analysis suggests the efficient level of monitoring, or probability of detecting
a wrong, decreases in a worker’s income stream and the intensity of suspension, at least whenmonitoring cost is relatively cheap. Under the modern system of internal governance and the
incentive scheme that encourages self-reporting, monitoring cost is considered arguably cheap.
Therefore, this result suggests excessive monitoring is unnecessary in the presence of highcompensation. On the same ground, this result motivates the life-cycle theory of efficientmonitoring: a younger firm should be monitored more frequently than an elder firm if a firm’s
compensation grows over time.

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Appendix
Preliminary analysis for stationary model: Because the value of an employee is time-invariant,equation (3) suggests
𝑈 = 𝜆𝑊 + (1 − 𝜆)𝛽𝑈.
Hence,
𝑊 − 𝑈 = Γ𝑊,
where Γ = (1 − 𝜆)(1 − 𝛽)/(1 − (1 − 𝜆)𝛽) . Then, 0 ≤ Γ ≤ 1 . Notice Γ = 0 when λ = 1 ,suggesting no imprisonment equates the value of being in and out of prison. Also, notice Γ = 1
when λ = 0, suggesting eternal imprisonment maximizes the relative value of being out of prison.
Then, equation (2) suggests(1 − 𝛽)𝑊 = ∫∞(𝑏 − 𝑝(𝑀)(𝛼𝑤 + 𝛽Γ𝑊 ))𝑟(𝑏)𝑑𝑏 + 𝑤.

𝑝(𝑀)(𝛼𝑤+𝛽Γ𝑊)

We start from analyzing how Γ is related to λ. We find:𝑑Γ/𝑑𝜆 < 0.
Next, we analyze how 𝑊 is related to 𝑀 and 𝑤, respectively. Recall:(1 − 𝛽)𝑊 = ∫∞(𝑏 − 𝑝(𝑀)(𝛼𝑤 + 𝛽Γ𝑊 ))𝑟(𝑏)𝑑𝑏 + 𝑤.

𝑝(𝑀)(𝛼𝑤+𝛽Γ𝑊)

Then, we find from this equation:∞(1 − 𝛽)𝜕𝑊/𝜕𝑀 = ∫(−𝑝′(𝑀)(𝛼𝑤 + 𝛽Γ𝑊 ) − 𝑝(𝑀)(𝛽Γ𝜕𝑊/𝜕𝑀))𝑟(𝑏)𝑑𝑏,

𝑝(𝑀)(𝛼𝑤+𝛽Γ𝑊)(1 − 𝛽)𝜕𝑊/𝜕𝑀 + 𝑝(𝑀)(𝛽Γ𝜕𝑊/𝜕𝑀) (1 − 𝑅(𝑏̃)) = − (1 − 𝑅(𝑏̃)) 𝑝′(𝑀)(𝛼𝑤 + 𝛽Γ𝑊 ),(1 − 𝛽 + 𝛽Γ𝑝(𝑀) (1 − 𝑅(𝑏̃))) 𝜕𝑊/𝜕𝑀 = − (1 − 𝑅(𝑏̃)) 𝑝′(𝑀)(𝛼𝑤 + 𝛽Γ𝑊 ),𝜕𝑊/𝜕𝑀 = − (1 − 𝑅(𝑏̃ )) 𝑝′(𝑀)(𝛼𝑤 + 𝛽Γ𝑊 )/ (1 − 𝛽 + 𝛽Γ𝑝(𝑀) (1 − 𝑅(𝑏̃))) < 0.

Also, we find from this equation:∞(1 − 𝛽)𝑑𝑊/𝑑𝑤 = ∫ (−𝑝′(𝑀)(𝛼𝑤 + 𝛽Γ𝑊 )𝑑𝑀/𝑑𝑤 − 𝑝(𝑀)(𝛼 + 𝛽Γ𝑑𝑊/𝑑𝑤))𝑟(𝑏)𝑑𝑏 + 1,𝑏̃

(1 − 𝛽)𝑑𝑊/𝑑𝑤 + 𝑝(𝑀)(𝛽Γ𝑑𝑊/𝑑𝑤) (1 − 𝑅(𝑏̃))= 1 − 𝛼𝑝(𝑀) (1 − 𝑅(𝑏̃)) − 𝑝′(𝑀)(𝛼𝑤 + 𝛽Γ𝑊 ) (1 − 𝑅(𝑏̃)) 𝑑𝑀/𝑑𝑤,(1 − 𝛽 + 𝛽Γ𝑝(𝑀) (1 − 𝑅(𝑏̃))) 𝑑𝑊/𝑑𝑤= 1 − 𝛼𝑝(𝑀) (1 − 𝑅(𝑏̃)) − 𝑝′(𝑀)(𝛼𝑤 + 𝛽Γ𝑊 ) (1 − 𝑅(𝑏̃)) 𝑑𝑀/𝑑𝑤,
𝑑𝑊/𝑑𝑤 = (1 − 𝛼𝑝(𝑀) (1 − 𝑅(𝑏̃))) / (1 − 𝛽 + 𝛽Γ𝑝(𝑀) (1 − 𝑅(𝑏̃))) + (𝜕𝑊/𝜕𝑀)(𝑑𝑀/𝑑𝑤).

Then,𝑑𝑊/𝑑𝑤 = 𝜕𝑊/𝜕𝑤 + (𝜕𝑊/𝜕𝑀)(𝑑𝑀/𝑑𝑤),
where𝜕𝑊/𝜕𝑤 = (1 − 𝛼𝑝(𝑀) (1 − 𝑅(𝑏̃))) / (1 − 𝛽 + 𝛽Γ𝑝(𝑀) (1 − 𝑅(𝑏̃))) ≥ 0.

Given the above, the first order condition with respect to monitoring level is rewritten by(𝑝′(𝑀)(𝛼𝑤 + 𝛽Γ𝑊) + 𝑝(𝑀)𝛽Γ(𝜕𝑊/𝜕𝑀))𝑟(𝑏̃) 𝑎̃ = 𝑐,(1 − 𝛽)𝑝′(𝑀)(𝛼𝑤 + 𝛽Γ𝑊)𝑟(𝑏̃) 𝑎̃/ (1 − 𝛽 + 𝛽Γ𝑝(𝑀) (1 − 𝑅(𝑏̃))) = 𝑐.
From this analysis, we conclude 𝑎̃∗ ≥ 0.
Proof for Proposition 2: From an envelope theorem,∞𝑑𝑆 /𝑑𝑤 = ∑ 𝛽 𝑡 𝑞 ∗ 𝑝(𝑀∗ )(𝛼 + 𝛽Γ𝜕𝑊/𝜕𝑤)𝑎̃∗ 𝑟(𝑏̃ ∗ ) ≥ 0.
∗

𝑡=0

Also,
∞

𝑑𝑆 /𝑑𝜆 = ∑ 𝛽 𝑡 𝑞 ∗ 𝑝(𝑀∗ )(𝛽𝑊𝑑Γ/𝑑𝜆)𝑎̃∗ 𝑟(𝑏̃ ∗ ) ≤ 0.
∗

𝑡=0Preliminary analysis for model with zero monitoring cost: Equation (2) together with equation(10) suggests
𝑊𝑡 = 𝑋 + 𝑤𝑡 + 𝛽𝑊𝑡+1 ,∞where 𝑋 = ∫𝐻−𝐵(𝑏 − (𝐻 − 𝐵))𝑟(𝑏)𝑑𝑏. Using this expression, equation (3) suggests(𝑊𝑡+1 − 𝑈𝑡+1 ) − (𝑊𝑡 − 𝑈𝑡 )= ((1 − 𝜆𝑡+1 )(𝑋 + 𝑤𝑡+1 ) − (1 − 𝜆𝑡 )(𝑋 + 𝑤𝑡 )+ 𝛽((1 − 𝜆𝑡+1 )(𝑊𝑡+2 − 𝑈𝑡+2 ) − (1 − 𝜆𝑡 )(𝑊𝑡+1 − 𝑈𝑡+1 ))).
From this relationship, we claim the following lemma.
Lemma 1: Suppose the social planner’s problem under zero monitoring cost and 𝑊𝑡 − 𝑈𝑡 ≥ 0 for
any 𝑡. If (𝑊𝑡+2 − 𝑈𝑡+2 ) − (𝑊𝑡+1 − 𝑈𝑡+1 ) ≥ 0, 𝑤𝑡+1 ≥ 𝑤𝑡 , and 𝜆𝑡+1 ≤ 𝜆𝑡 , then the following istrue: (𝑊𝑡+1 − 𝑈𝑡+1 ) − (𝑊𝑡 − 𝑈𝑡 ) ≥ 0. If (𝑊𝑡+2 − 𝑈𝑡+2 ) − (𝑊𝑡+1 − 𝑈𝑡+1 ) ≤ 0, 𝑤𝑡+1 ≤ 𝑤𝑡 , and𝜆𝑡+1 ≥ 𝜆𝑡 , then the following is true: (𝑊𝑡+1 − 𝑈𝑡+1 ) − (𝑊𝑡 − 𝑈𝑡 ) ≤ 0.
Proof: Obvious from the above equation.
Also, equation (3) suggests
𝑊𝑡 − 𝑈𝑡 = (1 − 𝜆𝑡 )(𝑋 + 𝑤𝑡 ) + 𝛽(1 − 𝜆𝑡 )(𝑊𝑡+1 − 𝑈𝑡+1 ).
From this relationship, we claim the following lemma.
Lemma 2: Suppose the social planner’s problem under zero monitoring cost. If 𝑊𝑡+1 − 𝑈𝑡+1 ≥ 0,
𝑊𝑡 − 𝑈𝑡 ≥ 0.
Proof: Obvious from the above equation.
The value gap between being employed and unemployed is recursively determined, given theterminal condition:
𝑊𝑇 − 𝑈𝑇 = (1 − 𝜆 𝑇 )(𝑋 + 𝑤𝑇 ) + 𝛽(1 − 𝜆 𝑇 )(𝑊 ∗ − 𝑈 ∗ ).
Proof for Proposition 3: Notice𝑊 ∗ − 𝑈 ∗ = 𝛽Γ𝑊 ∗ ≥ 0.
Then, Lemma 2 suggests, for any 𝑡,
𝑊𝑡 − 𝑈𝑡 ≥ 0,recursively.
Suppose 𝑤𝑡+1 ≥ 𝑤𝑡 , and 𝜆𝑡+1 ≤ 𝜆𝑡 for any 𝑡 . Then, because 𝑊 ∗ − 𝑈 ∗ = 𝛽Γ𝑊 ∗ ≥ 0 and𝑋 ≥ 0,

(𝑊𝑇+1 − 𝑈𝑇+1 ) − (𝑊𝑇 − 𝑈𝑇 )= (1 − 𝜆 𝑇+1 )(𝑋 + 𝑤𝑇+1 ) − (1 − 𝜆 𝑇 )(𝑋 + 𝑤𝑇 ) + 𝛽(𝜆 𝑇 − 𝜆 𝑇+1 )(𝑊 ∗ − 𝑈 ∗ ) ≥ 0.
Lemma 1 suggests, for any 𝑡,
𝛼𝑤𝑡 + 𝛽(𝑊𝑡+1 − 𝑈𝑡+1 ) ≥ 𝛼𝑤𝑡−1 + 𝛽(𝑊𝑡 − 𝑈𝑡 ),recursively. Then, equation (10) suggests, for any 𝑡,∗
𝑀𝑡∗ ≤ 𝑀𝑡−1.

The opposite is true if 𝑤𝑡+1 ≤ 𝑤𝑡 , and 𝜆𝑡+1 ≥ 𝜆𝑡 for any 𝑡.
Under the stationary version, equation (10) is replaced by𝑎̃ = 𝐻 − 𝑝(𝑀)(𝛼𝑤 + 𝛽Γ𝑊) − 𝐵 = 0.
Then the intersecting point of 𝑎̃ and the horizontal line at zero is 𝑀∗ . Notice the second ordercondition requires−𝑝′(𝑀)(𝛼𝑤 + 𝛽Γ𝑊) − 𝑝(𝑀)𝛽Γ𝜕𝑊/𝜕𝑀 ≤ 0,
meaning 𝑎̃ is a decreasing function in 𝑀. Also,−𝑝(𝑀)(𝛼 + 𝛽Γ ∂𝑊/𝜕𝑤) ≤ 0,
meaning 𝑎̃ shifts down by an increase in 𝑤. The intersection hence decreases by an increase in 𝑤.
From this observation, we conclude 𝑑𝑀∗ /𝑑𝑤 ≤ 0. On the other hand,−𝑝(𝑀)𝛽𝑊𝑑Γ/𝑑𝜆 ≥ 0,
meaning 𝑎̃ shifts up by an increase in 𝜆. The intersection hence increases by an increase in 𝜆.
From this observation, we conclude 𝑑𝑀∗ /𝑑𝜆 ≥ 0.

Proof for Proposition 7: In equation (15), if 𝑤/(1 − 𝑅(𝐻 − 𝐵)) ≥ 𝐻 − 𝐸[𝑏|𝑏 ≥ 𝐻 − 𝐵], theright-hand-side is non-positive. As 𝑝(𝑀∗ ) decreases, the right-hand-side decreases. From
Proposition 3, 𝑑𝑀∗ /𝑑𝑤 ≤ 0. Consequently, 𝑑𝐹 ∗ /𝑑𝑤 ≤ 0. On the other hand, if 𝑤/(1 − 𝑅(𝐻 −𝐵)) < 𝐻 − 𝐸[𝑏|𝑏 ≥ 𝐻 − 𝐵], the right-hand-side is positive. As 𝑝(𝑀∗ ) decreases, the right-handside increases. However, the right-hand-side also decreases, when 𝑤 increases, for fixed 𝑝(𝑀∗ ).
As these two effects oppose to each other, the effect of 𝑤 is ambiguous.