A Multivariate Analysis of the 2016 County-Level Presidential Vote and Turnout

We investigate the 2016 Presidential Election using the county as the unit of analysis to examine the variance in the percentage of votes cast for Clinton, Trump and voter turnout. Our independent variables conceptually relate to race, education, wellbeing, age, rural-urban continuum and international migration. We found that over 50% of the variance in vote outcome for Clinton and Trump is explained by race, education, economy and the physical health of the county population. Almost 50% of the variance in voter turnout is explained with the same variables plus age. The regression results showed that Trump voters tended to be more white, less educated, not poor, and unhealthy compared to Clinton voters.