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Optimal Dynamic Contracting

Author

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  • Marco Battaglini

    (Princeton University)

  • Rohit Lamba

    (Princeton University)

Abstract

We study a simple dynamic Principal-Agent model in which the agent?s types are serially correlated. In these models, the standard approach consists in first solving a relaxed version in which only local incentive compatibility constraints are considered, and then in proving that the local constraints are sufficient for implementability. We show that, with the exception of few notable examples highlighted in the literature, this approach is not generally valid: even assuming standard regularity conditions, both local and global incentive constraints are generally binding when serial correlation is sufficiently high. We uncover a number of interesting features of the optimal contract that cannot be observed in the special environments in which the standard approach works. Finally, we show that even in complex environments, approximately optimal allocations can be easily characterized by focusing on a particular class of contracts in which the allocation is forced to be monotonic.

Suggested Citation

  • Marco Battaglini & Rohit Lamba, 2012. "Optimal Dynamic Contracting," Working Papers 1431, Princeton University, Department of Economics, Econometric Research Program..
  • Handle: RePEc:pri:metric:wp046_2012_battaglini_lamba_optm_dyn_contract_10october2012_short.pdf
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    References listed on IDEAS

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    Cited by:

    1. Marina Halac & Pierre Yared, 2014. "Fiscal Rules and Discretion Under Persistent Shocks," Econometrica, Econometric Society, vol. 82(5), pages 1557-1614, September.
    2. Litterscheid, Sina & Szalay, Dezsö, 2014. "Sequential, multidimensional screening," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100621, Verein für Socialpolitik / German Economic Association.
    3. Terstiege, Stefan, 2013. "Precontractual Investigation and Sequential Screening," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 429, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    4. Sham M. Kakade & Ilan Lobel & Hamid Nazerzadeh, 2013. "Optimal Dynamic Mechanism Design and the Virtual-Pivot Mechanism," Operations Research, INFORMS, vol. 61(4), pages 837-854, August.
    5. Negin Golrezaei & Hamid Nazerzadeh, 2017. "Auctions with Dynamic Costly Information Acquisition," Operations Research, INFORMS, vol. 65(1), pages 130-144, February.
    6. Negin Golrezaei & Hamid Nazerzadeh & Ramandeep Randhawa, 2020. "Dynamic Pricing for Heterogeneous Time-Sensitive Customers," Manufacturing & Service Operations Management, INFORMS, vol. 22(3), pages 562-581, May.
    7. Andrzej Skrzypacz & Juuso Toikka, 2015. "Mechanisms for Repeated Trade," American Economic Journal: Microeconomics, American Economic Association, vol. 7(4), pages 252-293, November.
    8. Schottmüller, Christoph, 2015. "Adverse selection without single crossing: Monotone solutions," Journal of Economic Theory, Elsevier, vol. 158(PA), pages 127-164.
    9. Deb, Rahul & Said, Maher, 2015. "Dynamic screening with limited commitment," Journal of Economic Theory, Elsevier, vol. 159(PB), pages 891-928.
    10. Negin Golrezaei & Hamid Nazerzadeh, 2017. "Auctions with Dynamic Costly Information Acquisition," Operations Research, INFORMS, vol. 65(1), pages 130-144, February.
    11. Marco Battaglini, 2005. "Long-Term Contracting with Markovian Consumers," American Economic Review, American Economic Association, vol. 95(3), pages 637-658, June.

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    More about this item

    Keywords

    models; optimal allocation; complex environment;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles

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