Quarterly Journal of Political Science > Vol 10 > Issue 3

Targeting Political Advertising on Television

Mitchell Lovett, Simon School of Business, University of Rochester, USA, mitch.lovett@simon.rochester.edu Michael Peress, Department of Political Science, SUNY-Stony Brook, USA, michael.peress@stonybrook.edu
 
Suggested Citation
Mitchell Lovett and Michael Peress (2015), "Targeting Political Advertising on Television", Quarterly Journal of Political Science: Vol. 10: No. 3, pp 391-432. http://dx.doi.org/10.1561/100.00014107

Published: 17 Sep 2015
© 2015 M. Lovett and M. Peress
 
Subjects
Campaigns,  Electoral behavior,  Voting behavior,  Voting,  Microeconometrics,  Discrete choice modeling,  Econometric models
 

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In this article:
1. Relationship with Literature
2. Data
3. Identification Strategy
4. Estimation Procedure
5. Estimation Results
6. The Strategy Space and Targeting Opportunities
7. Candidate Strategies
Conclusions
References

Abstract

We study the targeting of political advertising by presidential candidates on television. For targeted advertising to have value, the audiences for television programs must differ in meaningful ways and advertising must be effective. We estimate a model of targeted advertising. Our results suggest the function of television advertising is primarily to persuade. Moreover, we find that there is sufficient variation in viewer characteristics across television programs to allow for effective targeting. The most effective targeting strategies therefore involve both parties adopting similar strategies of advertising primarily on programs with audiences containing many swing voters. Actual candidate behavior is largely consistent with this strategy indicating that candidates seem to accurately believe that the function of television advertising is to persuade voters. Nonetheless, we are able to uncover specific ways in which candidates could improve their advertising by identifying particularly effective shows and by quantifying the tradeoff between cost and effectiveness.

DOI:10.1561/100.00014107

Online Appendix | 100.00014107_app.zip (ZIP).

This is the article's accompanying appendix.

DOI: 10.1561/100.00014107_app

Replication Data | 100.00014107_supp.zip (ZIP).

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DOI: 10.1561/100.00014107_supp