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Testing Bayesian Updating with the AP Top 25

Daniel F. Stone

Bowdoin College - Department of Economics

July 1, 2011

Economic Inquiry, Forthcoming

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

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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

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References:  50
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