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Rationality of Belief

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  • Itzhak Gilboa
  • Andrew Postlewaite
  • David Schmeidler

Abstract

Economic theory reduces the concept of rationality to internal consistency. The practice of economics, however, distinguishes between rational and irrational beliefs. There is therefore an interest in a theory of rational beliefs, and of the process by which beliefs are generated and justified. We argue that the Bayesian approach is unsatisfactory for this purpose, for several reasons. First, the Bayesian approach begins with a prior, and models only a very limited form of learning, namely, Bayesian updating. Thus, it is inherently incapable of describing the formation of prior beliefs. Second, there are many situations in which there is not sufficient information for an individual to generate a Bayesian prior. It follows that the Bayesian approach is neither sufficient not necessary for the rationality of beliefs.
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Suggested Citation

  • Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2004. "Rationality of Belief," Levine's Bibliography 122247000000000690, UCLA Department of Economics.
  • Handle: RePEc:cla:levrem:122247000000000690
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    References listed on IDEAS

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    Cited by:

    1. Tigran Melkonyan & Mark Pingle, 2010. "Ambiguity, pessimism, and rational religious choice," Theory and Decision, Springer, vol. 69(3), pages 417-438, September.
    2. Ani Guerdjikova & John Quiggin, 2018. "Heuristic Modes of Decision Making and Survival in Financial Markets," Post-Print hal-02086267, HAL.
    3. Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2007. "Probabilities in Economic Modeling," PIER Working Paper Archive 07-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    4. Luigi Guiso & Paola Sapienza & Luigi Zingales, 2009. "Cultural Biases in Economic Exchange?," The Quarterly Journal of Economics, Oxford University Press, vol. 124(3), pages 1095-1131.
    5. Itzhak Gilboa & Offer Lieberman & David Schmeidler, 2012. "On the Definition of Objective Probabilities by Empirical Similarity," World Scientific Book Chapters, in: Case-Based Predictions An Axiomatic Approach to Prediction, Classification and Statistical Learning, chapter 11, pages 259-280, World Scientific Publishing Co. Pte. Ltd..
    6. Rossella Argenziano & Itzhak Gilboa, 2012. "History as a coordination device," Theory and Decision, Springer, vol. 73(4), pages 501-512, October.
    7. Luigi Guiso & Paola Sapienza & Luigi Zingales, 2010. "Civic Capital as the Missing Link," NBER Working Papers 15845, National Bureau of Economic Research, Inc.
    8. Gilboa, Itzhak & Postlewaite, Andrew & Schmeidler, David, 2009. "Is It Always Rational To Satisfy Savage'S Axioms?," Economics and Philosophy, Cambridge University Press, vol. 25(3), pages 285-296, November.
    9. Giocoli, Nicola, 2011. "From Wald to Savage: homo economicus becomes a Bayesian statistician," MPRA Paper 34117, University Library of Munich, Germany.
    10. Scott Condie & Jayant V. Ganguli, 2011. "Ambiguity and Rational Expectations Equilibria," Review of Economic Studies, Oxford University Press, vol. 78(3), pages 821-845.
    11. Ani Guerdjikova & John Quiggin, 2018. "Intertemporal Portfolio Choice with Incorrect Beliefs and Aversion to Surprise," Post-Print hal-02086151, HAL.
    12. Avdagic, Sabina, 2006. "One Path or Several? Understanding the Varied Development of Tripartism in New European Capitalisms," MPIfG Discussion Paper 06/5, Max Planck Institute for the Study of Societies.
    13. Pe[combining cedilla]ski, Marcin, 2011. "Prior symmetry, similarity-based reasoning, and endogenous categorization," Journal of Economic Theory, Elsevier, vol. 146(1), pages 111-140, January.
    14. Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2007. "Probabilities in Economic Modeling," PIER Working Paper Archive 07-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

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    JEL classification:

    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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