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Subjective Distributions

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  • Itzhak Gilboa

    ()

  • David Schmeidler

    ()

Abstract

A decision maker has to choose one of several random variables whose distributions are not known. As a Bayesian, she behaves as if she knew the distributions. In this paper we suggest an axiomatic derivation of these (subjective) distributions, which is more economical than the derivations by de Finetti or Savage. Whereas the latter derive the whole joint distribution of all the available random variables, our approach derives only the marginal distributions. Correspondingly, the preference questionnaire needed in our case is less smaller. Copyright Kluwer Academic Publishers 2004

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File URL: http://hdl.handle.net/10.1007/s11238-004-2596-7
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Bibliographic Info

Article provided by Springer in its journal Theory and Decision.

Volume (Year): 56 (2004)
Issue (Month): 4 (01)
Pages: 345-357

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Handle: RePEc:kap:theord:v:56:y:2004:i:4:p:345-357

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Web page: http://www.springerlink.com/link.asp?id=100341

Related research

Keywords: subjective probabilities; axiomatization; distributions;

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References

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  1. David Schmeidler, 2000. "Utility in Case-Based Decision Theory," Working Papers 00-06, Ohio State University, Department of Economics.
  2. Gilboa,Itzhak & Schmeidler,David, 2001. "A Theory of Case-Based Decisions," Cambridge Books, Cambridge University Press, number 9780521802345, October.
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Cited by:
  1. Karni, Edi, 2006. "Subjective expected utility theory without states of the world," Journal of Mathematical Economics, Elsevier, vol. 42(3), pages 325-342, June.

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