EconPapers    
Economics at your fingertips  
 

Bounded Rationality And Learning: A Framwork and A Robustness Result*

Aislinn Bohren and Daniel Hauser ()
Additional contact information
Daniel Hauser: Department of Economics, Aalto University

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

Abstract: We explore model misspecification in an observational learning framework. Individuals learn from private and public signals and the actions of others. An agent's type specifies her model of the world. Misspecified types have incorrect beliefs about the signal distribution, how other agents draw inference and/or others' payoffs. We establish that the correctly specified model is robust in that agents with approximately correct models almost surely learn the true state asymptotically. We develop a simple criterion to identify the asymptotic learning outcomes that arise when misspecification is more severe. Depending on the nature of the misspecification, learning may be correct, incorrect or beliefs may not converge. Different types may asymptotically disagree, despite observing the same sequence of information. This framework captures behavioral biases such as confirmation bias, false consensus effect, partisan bias and correlation neglect, as well as models of inference such as level-k and cognitive hierarchy.

Keywords: Social learning; model misspecification; bounded rationality (search for similar items in EconPapers)
JEL-codes: D82 D83 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cbe, nep-gth and nep-mic
Date: 2017-05-01, Revised 2017-05-01
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://economics.sas.upenn.edu/sites/default/files/filevault/SSRN%2017_007.pdf (application/pdf)

Related works:
Working Paper: Bounded Rationality And Learning: A Framework and A Robustness Result (2017) Downloads
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: https://EconPapers.repec.org/RePEc:pen:papers:17-007

Access Statistics for this paper

More papers in PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania 133 South 36th Street, Philadelphia, PA 19104. Contact information at EDIRC.
Bibliographic data for series maintained by Administrator ().

 
Page updated 2019-07-16
Handle: RePEc:pen:papers:17-007