Do Voters Learn from Presidential Election Campaigns?
Michael R. Alvarez and
Garrett Glasgow
No 1022, Working Papers from California Institute of Technology, Division of the Humanities and Social Sciences
Abstract:
Theory: 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. Hypothesis: 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. Data and Methods: We use panel survey data from the 1976 and 1980 presidential elections, combined with content analyses of the media during these same elections. Our primary analysis is conducted using random effects panel models. Results: 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 ow during each presidential campaign.
Pages: 44 pages
Date: 1997-10
References: Add references at CitEc
Citations:
Published:
Downloads: (external link)
http://www.hss.caltech.edu/SSPapers/wp1022.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found (http://www.hss.caltech.edu/SSPapers/wp1022.pdf [301 Moved Permanently]--> https://www.hss.caltech.edu/SSPapers/wp1022.pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:clt:sswopa:1022
Ordering information: This working paper can be ordered from
Working Paper Assistant, Division of the Humanities and Social Sciences, 228-77, Caltech, Pasadena CA 91125
Access Statistics for this paper
More papers in Working Papers from California Institute of Technology, Division of the Humanities and Social Sciences Working Paper Assistant, Division of the Humanities and Social Sciences, 228-77, Caltech, Pasadena CA 91125.
Bibliographic data for series maintained by Victoria Mason ().