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Knightian decision theory and econometric inferences

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  • Bewley, Truman F.

Abstract

An uncertainty averse Knightian decision maker has a set of probability distributions over outcomes and chooses something other than the status quo only if the change increases the expected payoff according to all the distributions. It is possible to define a standardized degree of uncertainty aversion. To each such degree, there corresponds a set of prior distributions over the parameters of a Gaussian linear regression model, these priors being centered on a uniform prior. The set of posterior means corresponding to this set of priors has the same properties as a standard confidence region.

Suggested Citation

  • Bewley, Truman F., 2011. "Knightian decision theory and econometric inferences," Journal of Economic Theory, Elsevier, vol. 146(3), pages 1134-1147, May.
  • Handle: RePEc:eee:jetheo:v:146:y:2011:i:3:p:1134-1147
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    References listed on IDEAS

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    1. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
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    Cited by:

    1. Wei-ling Chen & Leh-chyan So, 2014. "Validation of the Merton Distance to the Default Model under Ambiguity," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 7(1), pages 1-15, March.
    2. Corbae, Dean & Marimon, Ramon, 2011. "Introduction to Incompleteness and Uncertainty in Economics," Journal of Economic Theory, Elsevier, vol. 146(3), pages 775-784, May.
    3. Tamini, Lota D., 2012. "Optimal quality choice under uncertainty on market development," MPRA Paper 40845, University Library of Munich, Germany.
    4. Yehuda Izhakian & Zur Izhakian, 2015. "Decision making in phantom spaces," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 58(1), pages 59-98, January.
    5. Marc-Arthur Diaye & Gleb Koshevoy, 2011. "Random Sets Lotteries and Decision Theory," Documents de recherche 11-09, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.

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