Abstract

http://ssrn.com/abstract=1158052
 
 

References (50)



 
 

Citations (4)



 


 



Testing Bayesian Updating with the AP Top 25


Daniel F. Stone


Bowdoin College - Department of Economics

July 1, 2011

Economic Inquiry, Forthcoming

Abstract:     
Most studies of Bayesian updating use experimental data. This paper uses a non-experimental data source--the voter ballots of the Associated Press (AP) college football poll, a weekly subjective ranking of the top 25 teams--to test Bayes' rule as a descriptive model. I find that voters sometimes underreact to new information, sometimes overreact, and at other times their behavior is consistent with estimated Bayesian updating. A unifying explanation for the disparate results is that voters are more responsive to information that is more salient (i.e., noticeable). In particular, voters respond in a ``more Bayesian'' way to losses and wins over ranked teams, as compared to wins over unranked teams, and voters seem unaware of subtle variation in the precision of priors.

Number of Pages in PDF File: 38

Keywords: Belief Updating, Overreaction, Underreaction, Salience, Heuristics, College Football Rankings

JEL Classification: D80, D83, D84

Accepted Paper Series





Download This Paper

Date posted: July 11, 2008 ; Last revised: July 21, 2011

Suggested Citation

Stone, Daniel F., Testing Bayesian Updating with the AP Top 25 (July 1, 2011). Economic Inquiry, Forthcoming. Available at SSRN: http://ssrn.com/abstract=1158052

Contact Information

Daniel F. Stone (Contact Author)
Bowdoin College - Department of Economics ( email )
Brunswick, ME 04011
United States
6463387833 (Phone)
Feedback to SSRN


Paper statistics
Abstract Views: 932
Downloads: 126
Download Rank: 134,556
References:  50
Citations:  4

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo8 in 0.282 seconds