Is There a Golden Parachute in Sannikov’s Principal–Agent Problem?

Dylan Possamaï, Nizar Touzi

Research output: Contribution to journalArticlepeer-review

Abstract

This paper provides a complete review of the continuous-time optimal contracting problem introduced by Sannikov in the extended context allowing for possibly different discount rates for both parties. The agent’s problem is to seek for optimal effort given the compensation scheme proposed by the principal over a random horizon. Then, given the optimal agent’s response, the principal determines the best compensation scheme in terms of running payment, retirement, and lump-sum payment at retirement. A golden parachute is a situation where the agent ceases any effort at some positive stopping time and receives a payment afterward, possibly under the form of a lump-sum payment or of a continuous stream of payments. We show that a golden parachute only exists in certain specific circumstances. This is in contrast with the results claimed by Sannikov, where the only requirement is a positive agent’s marginal cost of effort at zero. In the general case, we prove that an agent with positive reservation utility is either never retired by the principal or retired above some given threshold (as in Sannikov’s solution). We show that different discount factors induce a facelifted utility function, which allows us to reduce the analysis to a setting similar to the equal-discount rates one. Finally, we also confirm that an agent with small reservation utility does have an informational rent, meaning that the principal optimally offers him a contract with strictly higher utility than his participation value.

Original languageEnglish (US)
Pages (from-to)1173-1203
Number of pages31
JournalMathematics of Operations Research
Volume50
Issue number2
DOIs
StatePublished - May 2025

Keywords

  • continuous-time principal agent
  • facelifting
  • optimal control and stopping

ASJC Scopus subject areas

  • General Mathematics
  • Computer Science Applications
  • Management Science and Operations Research

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