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Repeated moral hazard and recursive Lagrangeans

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  • Mele, Antonio

Abstract

This paper shows how to solve dynamic agency models by extending recursive Lagrangean techniques à la Marcet and Marimon (2011) to problems with hidden actions. The method has many advantages with respect to promised utilities approach (Abreu, Pearce and Stacchetti (1990)): it is a significant improvement in terms of simplicity, tractability and computational speed. Solutions can be easily computed for hidden actions models with several endogenous state variables and several agents, while the promised utilities approach becomes extremely difficult and computationally intensive even with just one state variable or two agents. Several numerical examples illustrate how this methodology outperforms the standard approach.

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  • Mele, Antonio, 2011. "Repeated moral hazard and recursive Lagrangeans," MPRA Paper 30310, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:30310
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    Cited by:

    1. Clementi, Gian Luca & Cooley, Thomas F. & Wang, Cheng, 2006. "Stock grants as a commitment device," Journal of Economic Dynamics and Control, Elsevier, vol. 30(11), pages 2191-2216, November.
    2. Marimon, Ramon & Werner, Jan, 2021. "The envelope theorem, Euler and Bellman equations, without differentiability," Journal of Economic Theory, Elsevier, vol. 196(C).
    3. Albert Marcet & Ramon Marimon, 2019. "Recursive Contracts," Econometrica, Econometric Society, vol. 87(5), pages 1589-1631, September.
    4. Messner Matthias & Pavoni Nicola & Sleet Christopher, "undated". "On the Dual Approach to Recursive Optimization," GSIA Working Papers 2012-E12, Carnegie Mellon University, Tepper School of Business.
    5. Wang, Cheng & Williamson, Stephen, 1996. "Unemployment insurance with moral hazard in a dynamic economy," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 44(1), pages 1-41, June.
    6. Emilio Espino & Julian Kozlowski & Juan M. Sanchez, 2013. "Too big to cheat: Efficiency and Investment in Partnerships," Working Papers 2013-001, Federal Reserve Bank of St. Louis.
    7. Espino, Emilio & Kozlowski, Julian & Sánchez, Juan M., 2018. "Investment and bilateral insurance," Journal of Economic Theory, Elsevier, vol. 176(C), pages 311-341.
    8. Matthias Messner & Nicola Pavoni & Christopher Sleet, "undated". "Contractive Dual Methods for Incentive Problems," GSIA Working Papers 2012-E26, Carnegie Mellon University, Tepper School of Business.
    9. Ramon Marimon & Eva Carceles-Poveda & Arpad Abraham, 2012. "On the optimal design of a Financial Stability Fund," 2012 Meeting Papers 945, Society for Economic Dynamics.
    10. Clayton, Christopher & Schaab, Andreas, 2022. "A Theory of Dynamic Inflation Targets," TSE Working Papers 22-1389, Toulouse School of Economics (TSE).
    11. Yunmin Chen & YiLi Chien & Michael T. Owyang, 2015. "Individual and Aggregate Constrained Efficient Intertemporal Wedges in Dynamic Mirrleesian Economies," Working Papers 2015-43, Federal Reserve Bank of St. Louis.
    12. Arie, Guy, 2016. "Dynamic costs and moral hazard: A duality-based approach," Journal of Economic Theory, Elsevier, vol. 166(C), pages 1-50.
    13. Charles Brendon, 2011. "Applying perturbation analysis to dynamic optimal tax problems," Economics Series Working Papers 581, University of Oxford, Department of Economics.
    14. Karol Mazur, 2020. "Sharing Risk to Avoid Tragedy: Informal Insurance and Irrigation in Village Economies," CSAE Working Paper Series 2020-19, Centre for the Study of African Economies, University of Oxford.
    15. Emilio Espino, 2012. "Investment and Insurance in an Economic Union," 2012 Meeting Papers 1176, Society for Economic Dynamics.

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    More about this item

    Keywords

    repeated moral hazard; collocation method; dynamic models with private information; recursive contracts;
    All these keywords.

    JEL classification:

    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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