Ideological Determinants of Voting Behavior in the 2016 US Presidential Election
The 2016 election marked a departure from previous elections, as identity became a more salient predictor of voter behavior than ever before. In this paper we use survey data from the Grinnell College National Poll to construct a predictive model of voter behavior in the 2016 election based on voter’s self-reported membership of various identity groups. We create a logistic regression model containing both the identity and demographic variables found to be important in previous literature in predicting a voter’s likelihood of voting for Trump.
We found that voters who identified as feminist or progressive were significantly less likely to vote for Trump, whereas believers in “America First” and gun rights or who identified as “politically incorrect” were more likely to vote for Trump. Our findings support previous research that found that ideological self-identification was a powerful predictor of voting behavior in the 2016 election.