DETERMINING WHO WILL SHOW UP AT THE POLLS on Election Day has long been a fascinating and complex field of study – for researchers and campaign consultants alike. While a high percentage of people proclaim their intent to vote, only a subset of them actually do, for a variety of reasons. A new research study co-authored by Harvard Kennedy School associate professor Todd Rogers provides new insight into this phenomenon, and suggests that specific campaign tactics could be deployed to incite voters to cast their ballots.
The study is published in the Proceedings of the National Academy of Science.
“People are regularly asked to report on their likelihoods of carrying out consequential future behaviors, including complying with medical advice, completing their educations and voting in upcoming elections,” the authors write. “Despite these stated self-predictions being notoriously unreliable, they are used to inform many strategic decisions.”
The research team reports on two studies examining the behavior of potential voters who self-report their intentions of going to the polls on Election Day. In both studies less than half of those citizens who predicted that they would vote actually did. What was even more interesting was the propensity for survey callers to predict with surprising certainly who would actually vote through the detection of non-verbal signals.
“We find that untrained survey callers’ predictions of who will vote meaningfully increases the statistical prediction of which respondents will follow through on their stated self-predictions – over and above respondents’ self-predictions,” the authors concluded. “Callers accomplish this by attending to signals of uncertainty and deception conveyed in respondents’ voices. These findings could improve political campaign resource allocation, and the targeting of interventions in domains including health and education.”
Todd Rogers is an associate professor of public policy at Harvard Kennedy School. Most of his current research sits at the intersection of education, psychology, judgment and decision-making, and behavioral economics. It aims to shed light on the cognitive, motivational, and social barriers to student achievement, and to develop low-cost scalable interventions that are informed by behavioral science.