Which Voters Will Be The Deciders of 2020?
The fast approaching 2018 election is a chance to put a check on Trump. But this analysis looks forward to the 2020 presidential race, which will set the course for our country into the future. The stakes could not be higher.
To understand how to beat Trump in 2020, it is instructive to look back on the electoral drivers in 2016. So we conducted a regression analysis of 2016 election results and voter file data. A regression analysis is a statistical process for estimating the relationship among variables. In this case, it isolates and illustrates the impact of different voter groups on Hillary Clinton's support in the 2016 presidential election. Voter file data was made available to us through the progressive data and analytics firm Catalist.*
* It is important to note, some voter file data comes from a national predictive model that is then applied to individual counties. In short, numbers should be considered estimates.
The regression analysis shows that the most impactful voter groups in 2016 were voters in diverse areas, who significantly boosted Clinton’s vote share, and a group of voters termed by Catalist to be “economically sensitive” voters, who hurt Clinton’s numbers nearly as much as voters in diverse places helped them. These economically sensitive voters can be defined as individuals with an overall sense of personal financial stress or uncertainty (a subjective measure different from acute economic hardship).
The lesson from this analysis is that to beat Trump in 2020, a candidate will need to engage voters of all races who live in diverse areas and win back economically sensitive voters, about half of whom are people of color. If 2016 is any indication, those two groups will make or break a winning coalition in 2020.