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TESTING BAYESIAN UPDATING WITH THE ASSOCIATED PRESS TOP 25
Author(s) -
STONE DANIEL F.
Publication year - 2013
Publication title -
economic inquiry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.823
H-Index - 72
eISSN - 1465-7295
pISSN - 0095-2583
DOI - 10.1111/j.1465-7295.2011.00431.x
Subject(s) - bayesian probability , prior probability , ranking (information retrieval) , salient , test (biology) , econometrics , bayes factor , bayesian inference , bayes' theorem , computer science , economics , artificial intelligence , paleontology , biology
Most studies of Bayesian updating use experimental data. This article uses a non‐experimental data source—the voter ballots of the Associated Press 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 . ( JEL D80, D83, D84)