Do Voters Learn from Presidential Election Campaigns?
Alvarez, R. Michael
We present a model of voter campaign learning
which is based on Bayesian learning models. This model assumes voters
are imperfectly informed and that they incorporate new information
into their existing perceptions about candidate issue positions in
a systematic manner. Additional information made available to
voters about candidate issue positions during the course of a political
campaign will lead voters to have more
precise perceptions of the issue positions of the candidates involved.
We use panel survey data from the 1976
and 1980 presidental elections, combined with content analyses of the
media during these same elections. Our primary analysis is
conducted using random effects panel models.
We find that during each of these campaigns
many voters became better informed about the positions of candidates
on many issues and that these changes in voter information are directly
related to the information flow during each presidential campaign.
presidential election campaigns
random effects panel models
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