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On dynamic programming with unbounded returns

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  • Duran, Jorge
Abstract
Some economic models like those of endogenous growth motivate the analysis of a class of recursive models sharing the property that the return function is not bounded along feasible paths. We consider a strategy of proof which allows to deal with many unbounded recursive models exploiting bounds to the rates of growth rather than to the levels.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Duran, Jorge, 1997. "On dynamic programming with unbounded returns," CEPREMAP Working Papers (Couverture Orange) 9710, CEPREMAP.
  • Handle: RePEc:cpm:cepmap:9710
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    File URL: http://www.cepremap.fr/depot/couv_orange/co9710.pdf
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    References listed on IDEAS

    as
    1. Streufert, Peter A., 1992. "An abstract topological approach to dynamic programming," Journal of Mathematical Economics, Elsevier, vol. 21(1), pages 59-88.
    2. 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.
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    Citations

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    Cited by:

    1. Le Van, Cuong & Morhaim, Lisa, 2002. "Optimal Growth Models with Bounded or Unbounded Returns: A Unifying Approach," Journal of Economic Theory, Elsevier, vol. 105(1), pages 158-187, July.
    2. Ghiglino, Christian, 2002. "Introduction to a General Equilibrium Approach to Economic Growth," Journal of Economic Theory, Elsevier, vol. 105(1), pages 1-17, July.
    3. V. Filipe Martins-da-Rocha & Yiannis Vailakis, 2013. "Fixed point for local contractions: Applications to recursive utility," International Journal of Economic Theory, The International Society for Economic Theory, vol. 9(1), pages 23-33, March.
    4. 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).
    5. Philippe Bich & Jean-Pierre Drugeon & Lisa Morhaim, 2018. "On Temporal Aggregators and Dynamic Programming," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01437496, HAL.
    6. Datta, Manjira & Mirman, Leonard J. & Morand, Olivier F. & Reffett, Kevin L., 2005. "Markovian equilibrium in infinite horizon economies with incomplete markets and public policy," Journal of Mathematical Economics, Elsevier, vol. 41(4-5), pages 505-544, August.
    7. Philippe Bich & Jean-Pierre Drugeon & Lisa Morhaim, 2018. "On temporal aggregators and dynamic programming," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 66(3), pages 787-817, October.
    8. Jorge Durán, 2003. "Discounting long run average growth in stochastic dynamic programs," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 22(2), pages 395-413, September.
    9. Le Van, Cuong & Cagri Saglam, H., 2004. "Optimal growth models and the Lagrange multiplier," Journal of Mathematical Economics, Elsevier, vol. 40(3-4), pages 393-410, June.
    10. 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.
    11. 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.
    12. 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.
    13. Suen, Richard M. H., 2009. "Bounding the CRRA Utility Functions," MPRA Paper 13260, University Library of Munich, Germany.
    14. Takashi Kamihigashi, 2014. "An order-theoretic approach to dynamic programming: an exposition," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 2(1), pages 13-21, April.
    15. 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.
    16. Bäuerle, Nicole & Jaśkiewicz, Anna, 2018. "Stochastic optimal growth model with risk sensitive preferences," Journal of Economic Theory, Elsevier, vol. 173(C), pages 181-200.
    17. Cuong Le Van & Lisa Morhaim & Yiannis Vailakis, 2008. "Monotone Concave Operators: An application to the existence and uniqueness of solutions to the Bellman equation," Working Papers hal-00294828, HAL.
    18. Cuong Le Van & Lisa Morhaim & Yiannis Vailakis, 2008. "Monotone concave operators: An application to the existence and uniqueness of solutions to the Bellman equation," Discussion Papers 0803, University of Exeter, Department of Economics.
    19. Łukasz Balbus & Anna Jaśkiewicz & Andrzej S. Nowak, 2020. "Equilibria in Altruistic Economic Growth Models," Dynamic Games and Applications, Springer, vol. 10(1), pages 1-18, March.
    20. Bloise, Gaetano & Vailakis, Yiannis, 2018. "Convex dynamic programming with (bounded) recursive utility," Journal of Economic Theory, Elsevier, vol. 173(C), pages 118-141.
    21. Alexis Akira Toda, 2024. "Unbounded Markov dynamic programming with weighted supremum norm Perov contractions," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 12(2), pages 141-156, December.
    22. Le Van, Cuong & Cagri Saglam, H., 2004. "Optimal growth models and the Lagrange multiplier," Journal of Mathematical Economics, Elsevier, vol. 40(3-4), pages 393-410, June.
    23. 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.

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    More about this item

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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