bayesian social learning conformity and stubbornness evidence from the ap top 25
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Bayesian Social Learning, Conformity, and Stubbornness: Evidence from the AP Top 25. Discussion. The plan. Objective: improve estimate of college-football ranking by as much as possible. Proxy for best estimate: voter’s own season-ending rankings.

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bayesian social learning conformity and stubbornness evidence from the ap top 25

Bayesian Social Learning, Conformity, and Stubbornness: Evidence from the AP Top 25

Discussion

the plan
The plan
  • Objective: improve estimate of college-football ranking by as much as possible.
  • Proxy for best estimate: voter’s own season-ending rankings.
  • Information production: each week’s results and aggregate rankings lead to updated rankings by each voter.
  • Research question: to what extent are updates rational?
slide3

College football presents an unusually poor data set for measuring learning over the season, because of small number of games, the way ranked teams strategically avoid scheduling strong nonconference opponents, and the fact that there is no playoff system.

  • In addition, it is not clear that football rankings are obviously transitive.
  • The assumption that final scores are the only in-game information needed to update rankings, if false, means that estimates of Bayesian learning are biased downward.
slide4

If voters care about their reputation, why isn’t matching the season-ending aggregate rankings the objective?

slide5

Another method exists to test financial effects of reputation, namely polls in less lucrative sports. These sports, having playoffs, also provide perhaps a better measure of the accuracy objective than college football.

  • In particular, predictions of NCAA basketball tournament outcomes at Yahoo, etc. often allow voters to update their brackets after each round. Here, the outcome to be best estimated – the final tournament results in all rounds – is obvious and uncontroversial.
slide6

Why use AggB and AggW, which are crude measures of social information? Why not use difference between voter’s and aggregate ranking?

slide7

The fact that inexperienced voters respond more strongly to social information could be a rational acknowledgment of poor information as much as a greater concern for reputation.

slide9

Do nationally televised games generate more under-response to social information? If voters are stubborn, I expect they would.

minor stuff
Minor stuff
  • Voter “tastes regarding true ranings” seems a peculiar phrase, and I’m not sure what it means.
  • It’s not clear how “YTD performance” is different from “the best estimate of the rankings at the end of the season, based on what we know now.”
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