Supplementary Appendix for ‘Non-Bayesian Updating: A Theoretical Framework’

Larry Epstein (), Jawwad Noor () and Alvaro Sandroni ()
Additional contact information
Alvaro Sandroni: Department of Economics, University of Pennsylvania

PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania

Abstract: This appendix applies the model in ”Non-Bayesian Updating: A Theoretical Frame-Work” to address the question: What do non-Bayesian updaters learn?

Keywords: Non-Bayesian; Learning (search for similar items in EconPapers)
JEL-codes: C70 C12 D81 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba and nep-gth
Date: 2008-01-18
View list of references

Downloads: (external link)
http://economics.sas.upenn.edu/system/files/08-017.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:pen:papers:08-017

Access Statistics for this paper

More papers in PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania
Address: 3718 Locust Walk, Philadelphia, PA 19104
Contact information at EDIRC.
Series data maintained by Dolly Guarini ().