Learning under Ambiguity: An Experiment in Gradual Information Processing
Published: 25 May 2021| Version 1 | DOI: 10.17632/r7sstyvsmp.1
Contributor:
Kathleen NgangoueDescription
This experiment studies belief updating under ambiguity, using subjects' bid and ask prices for an asset with ambiguous payoff distribution. Bid and ask quotes allow for distinguishing between the two main paradigms of updating under ambiguity--full Bayesian updating and maximum likelihood updating. We find substantial heterogeneity in subjects' reaction to information. The majority of subjects (54\%) chose quotes that were in line with full Bayesian updating, while another, non-negligible, group (35\%) behaved like maximum likelihood updaters. (JEL: G11, C91, D81)
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Institutions
New York University
Categories
Social Sciences