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Knightian Decision Theory, Part II. Intertemporal Problems

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Abstract

The theory of choice proposed in "Knightian Decision Theory, Part I" is here applied to intertemporal problems. An analogue of dynamic programming called maxmin programming is developed. Also, it is shown that detailed contingent planning may not be needed in order to achieve maximality, a program being maximal if no other program is preferred to it. In certain circumstances, a maximal program can be achieved by making a finite calculation in each period. This calculation ignores distant future states and could also ignore unlikely contingencies. A decision maker making such calculations would behave much like a satisficer.

Suggested Citation

  • Truman F. Bewley, 1987. "Knightian Decision Theory, Part II. Intertemporal Problems," Cowles Foundation Discussion Papers 835, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:835
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    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d08/d0835.pdf
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    1. Mordechai I. Henig, 1985. "The Principle of Optimality in Dynamic Programming with Returns in Partially Ordered Sets," Mathematics of Operations Research, INFORMS, vol. 10(3), pages 462-470, August.
    2. Truman F. Bewley, 1986. "Knightian Decision Theory: Part 1," Cowles Foundation Discussion Papers 807, Cowles Foundation for Research in Economics, Yale University.
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    Cited by:

    1. Jean-Marc Bonnisseau & Lalaina Rakotonindrainy, 2015. "A note on the characterization of optimal allocations in OLG models with multiple goods," Post-Print halshs-01158117, HAL.
    2. Rigotti, L., 1998. "Imprecise Beliefs in a Principal Agent Model," Discussion Paper 1998-128, Tilburg University, Center for Economic Research.
    3. Adam Cagliarini & Alexandra Heath, 2000. "Monetary Policy-making in the Presence of Knightian Uncertainty," RBA Research Discussion Papers rdp2000-10, Reserve Bank of Australia.
    4. Spanjers, Willy, 2008. "Central banks and ambiguity," International Review of Economics & Finance, Elsevier, vol. 17(1), pages 85-102.
    5. Hugo Benítez-Silva & Debra Dwyer & Wayne-Roy Gayle & Thomas Muench, 2008. "Expectations in micro data: rationality revisited," Empirical Economics, Springer, vol. 34(2), pages 381-416, March.
    6. Lopomo, Giuseppe & Rigotti, Luca & Shannon, Chris, 2011. "Knightian uncertainty and moral hazard," Journal of Economic Theory, Elsevier, vol. 146(3), pages 1148-1172, May.
    7. Leandro Nascimento, 2011. "Remarks on the consumer problem under incomplete preferences," Theory and Decision, Springer, vol. 70(1), pages 95-110, January.
    8. Faro, José Heleno & Lefort, Jean-Philippe, 2019. "Dynamic objective and subjective rationality," Theoretical Economics, Econometric Society, vol. 14(1), January.
    9. Lorenzo Bastianello & Jos'e Heleno Faro & Ana Santos, 2020. "Dynamically Consistent Objective and Subjective Rationality," Papers 2004.12347, arXiv.org.
    10. Wisnicki, Bartlomiej, 2022. "Consumer inertia fosters product quality," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 96(C).
    11. Lo, Kin Chung, 2000. "Epistemic conditions for agreement and stochastic independence of [epsi]-contaminated beliefs," Mathematical Social Sciences, Elsevier, vol. 39(2), pages 207-234, March.
    12. William A. Brock, 2006. "Profiling Problems With Partially Identified Structure," Economic Journal, Royal Economic Society, vol. 116(515), pages 427-440, November.
    13. Christopher P Chambers & Federico Echenique, 2021. "Empirical Welfare Economics," Papers 2108.03277, arXiv.org, revised Sep 2022.
    14. Kraus, Alan & Sagi, Jacob S., 2006. "Inter-temporal preference for flexibility and risky choice," Journal of Mathematical Economics, Elsevier, vol. 42(6), pages 698-709, September.
    15. Robert Chambers & Tigran Melkonyan, 2008. "Eliciting beliefs," Theory and Decision, Springer, vol. 65(4), pages 271-284, December.
    16. Hansen, Lars Peter & Sargent, Thomas J., 2011. "Robustness and ambiguity in continuous time," Journal of Economic Theory, Elsevier, vol. 146(3), pages 1195-1223, May.
    17. Shabnam Mousavi & Gerd Gigerenzer, 2017. "Heuristics are Tools for Uncertainty," Homo Oeconomicus: Journal of Behavioral and Institutional Economics, Springer, vol. 34(4), pages 361-379, December.
    18. Lorenzo Bastianello & José Heleno Faro & Ana Santos, 2022. "Dynamically consistent objective and subjective rationality," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 74(2), pages 477-504, September.
    19. Maxim Raginsky & Angelia Nedić, 2016. "Online Discrete Optimization in Social Networks in the Presence of Knightian Uncertainty," Operations Research, INFORMS, vol. 64(3), pages 662-679, June.
    20. Kin Chung Lo, 1998. "Epistemic Conditions for Agreement and Stochastic Independence of epsilon-Contaminated Beliefs," Working Papers 1998_02, York University, Department of Economics.
    21. Brock,W.A., 2003. "Tipping points, abrupt opinion changes, and punctuated policy change," Working papers 28, Wisconsin Madison - Social Systems.
    22. Robert G. Chambers & Tigran A. Melkonyan, 2010. "Regulatory Policy Design in an Uncertain World," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 12(6), pages 1081-1107, December.

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