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. Third, this lack of information is even more acute when we address the beliefs that can be attributed to a society. We hold that one needs to explore other approaches to the representation of information and of beliefs, which may be helpful in describing the formation of Bayesian as well as non-Bayesian beliefs.
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Enriqueta Aragones & Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2003.
"Fact-Free Learning,"
PIER Working Paper Archive
05-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Dec 2004.
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Enriqueta Aragones & Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2003.
"Fact-Free Learning,"
PIER Working Paper Archive
03-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
[Downloadable!]
Enriqueta Aragones & Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2005.
"Fact-Free Learning,"
American Economic Review,
American Economic Association, vol. 95(5), pages 1355-1368, December.
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