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A principal-agent model of sequential testing

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    (Collegio Carlo Alberto)

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    (Toulouse School of Economics)

Abstract
This paper analyzes the optimal provision of incentives in a dynamic information acquisition process. In every period, the agent can acquire costly information that is relevant to the principal's decision. Each signal may or may not provide definitive evidence in favor of the good state. Neither the agent's effort nor the realizations of his signals are observable. First, we assume that the agent has no private information at the time of contracting. Under the optimal mechanism, the agent is rewarded only when his messages are consistent with the state. The payments that the agent receives when he correctly announces the good state increase over time. We then characterize the optimal mechanisms when the agent has superior information about the state at the outset of the relationship. The principal prefers to offer different contracts if and only if the agent types are sufficiently diverse. Finally, all agent types benefit from their initial private information.

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  • , & ,, 2012. "A principal-agent model of sequential testing," Theoretical Economics, Econometric Society, vol. 7(3), September.
    • Handle: RePEc:the:publsh:914
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    Cited by:

    1. Johannes Hörner & Larry Samuelson, 2013. "Incentives for experimenting agents," RAND Journal of Economics, RAND Corporation, vol. 44(4), pages 632-663, December.
    2. Jin Hyuk Choi & Kookyoung Han, 2023. "Delegation of information acquisition, information asymmetry, and outside option," International Journal of Game Theory, Springer;Game Theory Society, vol. 52(3), pages 833-860, September.
    3. Catherine Bobtcheff & Raphaël Levy, 2017. "More Haste, Less Speed? Signaling through Investment Timing," American Economic Journal: Microeconomics, American Economic Association, vol. 9(3), pages 148-186, August.
    4. Rodivilov, Alexander, 2022. "Monitoring innovation," Games and Economic Behavior, Elsevier, vol. 135(C), pages 297-326.
    5. Chen, Chia-Hui & Ishida, Junichiro, 2018. "Hierarchical experimentation," Journal of Economic Theory, Elsevier, vol. 177(C), pages 365-404.
    6. Nicolas Klein & Tymofiy Mylovanov, 2011. "Should the Flatterers be Avoided?," 2011 Meeting Papers 1273, Society for Economic Dynamics.
    7. Gomes, Renato & Gottlieb, Daniel & Maestri, Lucas, 2016. "Experimentation and project selection: Screening and learning," Games and Economic Behavior, Elsevier, vol. 96(C), pages 145-169.
    8. Carroll, Gabriel, 2019. "Robust incentives for information acquisition," Journal of Economic Theory, Elsevier, vol. 181(C), pages 382-420.
    9. Chia‐Hui Chen & Junichiro Ishida, 2018. "Dynamic performance evaluation with deadlines: The role of commitment," Journal of Industrial Economics, Wiley Blackwell, vol. 66(2), pages 377-422, June.
    10. Khalil, Fahad & Lawarree, Jacques & Rodivilov, Alexander, 2020. "Learning from failures: Optimal contracts for experimentation and production," Journal of Economic Theory, Elsevier, vol. 190(C).
    11. Achim, Peter, 2024. "Innovation through competitive experimentation," Journal of Mathematical Economics, Elsevier, vol. 111(C).
    12. Gao, Hong & Xu, Haibo, 2020. "Learning, belief manipulation and optimal relationship termination," Economics Letters, Elsevier, vol. 190(C).
    13. Chia-Hui Chen & Junichiro Ishida, 2015. "A Tenure-Clock Problem," ISER Discussion Paper 0919, Institute of Social and Economic Research, Osaka University.
    14. Samuel Häfner & Curtis R. Taylor, 2022. "On young Turks and yes men: optimal contracting for advice," RAND Journal of Economics, RAND Corporation, vol. 53(1), pages 63-94, March.
    15. Alessandro Spiganti, 2020. "Can Starving Start‐ups Beat Fat Labs? A Bandit Model of Innovation with Endogenous Financing Constraint," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(2), pages 702-731, April.

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    More about this item

    Keywords

    Dynamic mechanism design; information acquisition; sequential testing;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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