Principal-Agent Problems with Exit Options
Identifieur interne : 000185 ( Main/Exploration ); précédent : 000184; suivant : 000186Principal-Agent Problems with Exit Options
Auteurs : Jaksa Cvitanic [États-Unis] ; Xuhu Wan [Hong Kong] ; Jianfeng Zhang [États-Unis]Source :
- The B.E. Journal of Theoretical Economics [ 1935-1704 ] ; 2008-10-06.
Abstract
We consider the problem of when to deliver the contract payoff, in a continuous-time principal-agent setting, in which the agent's effort is unobservable. The principal can design contracts of a simple form that induce the agent to ask for the payoff at the time of the principal's choosing. The optimal time of payment depends on the agent's and the principal's outside options. We develop a theory for general utility functions, while with CARA utilities we are able to specify conditions under which the optimal payment time is not random. However, in general, the optimal payment time is typically random. One illustrative application is the case when the agent can be fired, after having been paid a severance payment, and then replaced by another agent. The methodology we use is the stochastic maximum principle and its link to Forward-Backward Stochastic Differential Equations.
Url:
DOI: 10.2202/1935-1704.1474
Affiliations:
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<front><div type="abstract" xml:lang="en">We consider the problem of when to deliver the contract payoff, in a continuous-time principal-agent setting, in which the agent's effort is unobservable. The principal can design contracts of a simple form that induce the agent to ask for the payoff at the time of the principal's choosing. The optimal time of payment depends on the agent's and the principal's outside options. We develop a theory for general utility functions, while with CARA utilities we are able to specify conditions under which the optimal payment time is not random. However, in general, the optimal payment time is typically random. One illustrative application is the case when the agent can be fired, after having been paid a severance payment, and then replaced by another agent. The methodology we use is the stochastic maximum principle and its link to Forward-Backward Stochastic Differential Equations.</div>
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