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Optimal Compensation Contracts for Optimistic Managers

Author

Listed:
  • Giovanni Immordino

    (Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno)

  • Anna Maria C. Menichini

    (Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno)

  • Maria Grazia Romano

    (Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno)

Abstract

We study an employment contract between an (endogenously) optimistic manager and realistic investors. The manager faces a trade-off between ensuring that effort reflects accurate news and savoring emotionally beneficial good news. Investors and manager agree on optimal recollection when the weight the manager attaches to anticipatory utility is small. For intermediate values investors bear an extra-cost to make the manager recall bad news. For large weights investors renounce inducing signal recollection. We extend the analysis to the case in which anticipatory utility is the manager’s private information and derive testable predictions on the relationship between personality traits, managerial compensation and recruitment policies

Suggested Citation

  • Giovanni Immordino & Anna Maria C. Menichini & Maria Grazia Romano, 2012. "Optimal Compensation Contracts for Optimistic Managers," Working Papers 3_224, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
    • Handle: RePEc:sep:wpaper:3_224
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    File URL: http://www.dises.unisa.it/RePEc/sep/wpaper/3_224.pdf
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    References listed on IDEAS

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    Cited by:

    1. Immordino, Giovanni & Menichini, Anna Maria C. & Romano, Maria Grazia, 2011. "A simple impossibility result in behavioral contract theory," Economics Letters, Elsevier, vol. 113(3), pages 307-309.

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    More about this item

    Keywords

    Over-optimism; managerial compensation; anticipatory utility;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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