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Modèle Principal-Agent×Mécanisme VCG×
DomaineThéorie des jeuxThéorie des jeux
FamilleMachine learningMachine learning
Année d'origine19761961
Auteur d'origineMichael Jensen, William Meckling, Bengt HolmstromWilliam Vickrey, Edward Clarke, Theodore Groves
Typealgorithmalgorithm
Source fondatriceJensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3(4), 305-360. DOI ↗Vickrey, W. (1961). Counterspeculation, auctions, and competitive sealed bids. The Journal of Finance, 16(1), 8-37. DOI ↗
AliasAgency Theory, Hidden Action Problem, Moral HazardVickrey Mechanism, Generalized Vickrey Auction, Truthful Mechanism
Apparentées44
RésuméThe Principal-Agent Model analyzes how a principal (e.g., owner, employer, policymaker) can incentivize an agent (e.g., manager, employee, firm) to act in the principal's interest when the agent has private information or can take hidden actions. Formalized by Jensen and Meckling in 1976, the model identifies agency costs arising from moral hazard (the agent exerts less effort than desired) and adverse selection (the agent hides unfavorable information). Optimal contracts balance incentives with risk allocation.The Vickrey-Clarke-Groves (VCG) Mechanism is a truthful mechanism design solution that allocates resources and determines payments to incentivize participants to reveal their true valuations. Building on William Vickrey's 1961 sealed-bid auction work and extended by Clarke and Groves, VCG ensures that reporting truth is a dominant strategy for all participants, achieving allocative efficiency while maximizing total surplus.
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ScholarGateComparer des méthodes: Principal-Agent Model · VCG Mechanism. Consulté le 2026-06-19 sur https://scholargate.app/fr/compare