Why Vote in Person in a Pandemic? Using Machine Learning to Predict Voting Methods

What spurs voters to vote in person, despite an established universal vote-by-mail (VBM) system and a once-in-a-century pandemic? We explore this question with official voter data from Colorado, a vote-by-mail state since 2013, but where 6% of voters still vote in person. Using multiclass classification, we analyze (1) the choice between voting by mail (VBM), voting in person, and not voting in the 2020 general election, and (2) the choice to switch to in-person voting despite having used VBM in previous cycles. The results suggest that the choice of voting modes is mainly habitual, and local variations of COVID-19 and demographics hardly mattered. Notably, Republican partisanship plays an important role in predicting "switchers" to in-person voting; indeed, the probability of switching to in-person voting was 5.2% conditional on being a Republican as opposed to 1.9% conditional on being a Democrat.