Machine learningGame TheoryGame-theoreticAlgorithm

Principal-Agent Model

Also known as: Agency Theory, Hidden Action Problem, Moral Hazard

OriginatorMichael Jensen, William Meckling, Bengt HolmstromYear1976Sources2Related methods11

The 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.

Key highlights

  • Explains agency costs in hierarchical organizations and their impact on efficiency
  • Provides framework for optimal incentive design balancing incentives against risk
  • Extends to adverse selection, multi-tasking, and career concerns
  • Highly applicable to real contracts (executive compensation, sharecropping, insurance deductibles)

Intuition

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How it works

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When to use it

Apply principal-agent analysis when designing contracts for employment, management compensation, procurement, regulation, or insurance. Use when actions are unobservable and agents might otherwise act against the principal's interest. Important in corporate governance (aligning manager and shareholder interests), public sector management (monitoring civil servants), and financial contracts (incentivizing effort).

Strengths & limitations

Strengths
  • Explains agency costs in hierarchical organizations and their impact on efficiency
  • Provides framework for optimal incentive design balancing incentives against risk
  • Extends to adverse selection, multi-tasking, and career concerns
  • Highly applicable to real contracts (executive compensation, sharecropping, insurance deductibles)
Limitations
  • Assumes principal observes outcome; when outcomes are unobservable or highly delayed, contracts are harder to design
  • Assumes agent risk-averse; risk-neutral agents may not require as much incentive dampening
  • Does not address multi-agent settings where agents interact (team moral hazard)
  • Requires cardinal utility and specific distributional assumptions; comparative statics are sensitive to assumptions

Common pitfalls

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Applications

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Frequently asked

Why does the principal not simply monitor the agent to observe effort?

Monitoring is costly and often infeasible. Effort is typically unobservable (the agent works remotely), or monitoring costs exceed the benefits of eliminating moral hazard. Contracts that condition pay on observable outcomes (like profits) provide incentives at lower cost.

What is the difference between moral hazard and adverse selection?

Moral hazard occurs after a contract is signed: the agent takes hidden actions that worsen the principal's payoff. Adverse selection occurs before contracting: the agent has hidden information about type (e.g., ability) that the principal cannot verify. Both require incentive-compatible contracts but at different stages.

Why do optimal contracts often tie pay to imperfect outcome measures?

Because perfect measures of effort are infeasible. Tying pay to noisy outcome measures (e.g., firm profit) imperfectly incentivizes effort but exposes the agent to random outcome fluctuations. The optimal contract balances incentive strength against risk exposure.

Sources

  1. 1.
    Jensen, 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.
  2. 2.
    Holmstrom, B. (1991). The firm as a subpoena server. Journal of Law, Economics and Organization, 7(2), 53-64.

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ScholarGate. (2026, June 3). Principal-Agent Model. ScholarGate. https://scholargate.app/game-theory/principal-agent-model

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