Information, the Economy, and the Primaries: An Overlooked Contributor to Candidate Preference

26 Pages Posted: 30 Apr 2016 Last revised: 17 Nov 2016

See all articles by Peter Beattie

Peter Beattie

University of California, Irvine, Department of Political Science, Students

Date Written: April 28, 2016

Abstract

Within research on political preferences, specific knowledge about various issue areas is an under-researched predictor. In this article, the joint effects of specific knowledge about the current state of the US economy and standard demographic and ideological variables are investigated in a sample of 740 American internet users. Using a technique from signal detection theory, economic knowledge, along with demographic and ideological variables, is found to predict candidate preferences – but in different ways among Democrats and Republicans. Among Democrats, greater knowledge of negative aspects of the economy predicts support for Sanders over Clinton; among Republicans, greater knowledge of positive and negative aspects of the economy predicts support for Establishment candidates over Trump. Additionally, data from both survey respondents and county-level primary voting data are examined for effects of internet use on candidate preference, finding in both datasets a correlation between support for Sanders and internet use. The findings are discussed with regard to some of the surprising developments in the early 2016 US presidential race.

Keywords: Preferences, primaries, information, knowledge, meme, social representations, economy

Suggested Citation

Beattie, Peter, Information, the Economy, and the Primaries: An Overlooked Contributor to Candidate Preference (April 28, 2016). Available at SSRN: https://ssrn.com/abstract=2772211 or http://dx.doi.org/10.2139/ssrn.2772211

Peter Beattie (Contact Author)

University of California, Irvine, Department of Political Science, Students ( email )

Irvine, CA
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
46
Abstract Views
471
PlumX Metrics