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On Temporal Aggregators and Dynamic Programming

Author

Listed:
  • Philippe Bich

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Jean-Pierre Drugeon

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique)

  • Lisa Morhaim

    (CRED - Centre de Recherche en Economie et Droit - UP2 - Université Panthéon-Assas)

Abstract

This paper proposes dynamic programming tools for payoffs based on aggregating functions that depend on the current action and the future expected payoff. Some regularity properties are provided on the aggregator to establish existence, uniqueness and computation of the solution to the Bellman equation. Our setting allows to encompass and generalize many previous results based upon additive or non-additive payoff functions.

Suggested Citation

  • Philippe Bich & Jean-Pierre Drugeon & Lisa Morhaim, 2018. "On Temporal Aggregators and Dynamic Programming," Post-Print halshs-01437496, HAL.
    • Handle: RePEc:hal:journl:halshs-01437496
    DOI: 10.1007/s00199-017-1045-0
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01437496
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    References listed on IDEAS

    as
    1. Takashi Kamihigashi, 2014. "Elementary results on solutions to the bellman equation of dynamic programming: existence, uniqueness, and convergence," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 56(2), pages 251-273, June.
    2. Le Van, Cuong & Vailakis, Yiannis, 2005. "Recursive utility and optimal growth with bounded or unbounded returns," Journal of Economic Theory, Elsevier, vol. 123(2), pages 187-209, August.
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    6. Janusz Matkowski & Andrzej Nowak, 2011. "On discounted dynamic programming with unbounded returns," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 46(3), pages 455-474, April.
    7. Peter A. Streufert, 1990. "Stationary Recursive Utility and Dynamic Programming under the Assumption of Biconvergence," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(1), pages 79-97.
    8. Juan Rincón-Zapatero & Carlos Rodríguez-Palmero, 2007. "Recursive utility with unbounded aggregators," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 33(2), pages 381-391, November.
    9. Masayuki Yao, 2016. "Recursive Utility and the Solution to the Bellman Equation," Discussion Paper Series DP2016-08, Research Institute for Economics & Business Administration, Kobe University.
    10. Juan Pablo RincÛn-Zapatero & Carlos RodrÌguez-Palmero, 2003. "Existence and Uniqueness of Solutions to the Bellman Equation in the Unbounded Case," Econometrica, Econometric Society, vol. 71(5), pages 1519-1555, September.
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    12. Boud, John III, 1990. "Recursive utility and the Ramsey problem," Journal of Economic Theory, Elsevier, vol. 50(2), pages 326-345, April.
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    15. V. Filipe Martins-da-Rocha & Yiannis Vailakis, 2010. "Existence and Uniqueness of a Fixed Point for Local Contractions," Econometrica, Econometric Society, vol. 78(3), pages 1127-1141, May.
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    Cited by:

    1. Balbus, Łukasz & Reffett, Kevin & Woźny, Łukasz, 2022. "Time-consistent equilibria in dynamic models with recursive payoffs and behavioral discounting," Journal of Economic Theory, Elsevier, vol. 204(C).
    2. Bloise, G. & Van, C. Le & Vailakis, Y., 2024. "An approximation approach to dynamic programming with unbounded returns," Journal of Mathematical Economics, Elsevier, vol. 111(C).
    3. Jean-Pierre Drugeon & Thai Ha-Huy & Thi Do Hanh Nguyen, 2019. "On maximin dynamic programming and the rate of discount," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 67(3), pages 703-729, April.
    4. Antoine Riche & Francesco Magris & Daria Onori, 2020. "Monetary rules in a two-sector endogenous growth model," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 69(4), pages 1049-1100, June.
    5. Łukasz Balbus, 2020. "On recursive utilities with non-affine aggregator and conditional certainty equivalent," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 70(2), pages 551-577, September.
    6. Rabah Amir, 2018. "Special issue: supermodularity and monotone methods in economics," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 66(3), pages 547-556, October.
    7. Gaetano Bloise & Cuong Le Van & Yiannis Vailakis, 2024. "Do not Blame Bellman: It Is Koopmans' Fault," Econometrica, Econometric Society, vol. 92(1), pages 111-140, January.
    8. Guanlong Ren & John Stachurski, 2018. "Dynamic Programming with Recursive Preferences: Optimality and Applications," Papers 1812.05748, arXiv.org, revised Jun 2020.

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    More about this item

    Keywords

    Temporal Aggregators; Intertemporal Choice; Dynamic Programming;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General

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