Snap Judgments: Predicting Politician Competence from Photos

Seminal studies show that naive lab participants accurately predict who wins real-world elections based solely on candidate photos. It is unclear what this implies for the health of democracy without knowing whether candidates who look more electable or competent in photos behave more competently in office. This study brings novel performance data to this question and shows that voters can identify which politicians divert less public money and communicate more persuasively based solely on headshots. Such inferences do not predict politicians' effort visiting their constituencies, but neither do other available metrics like professional qualifications. I implement these studies in a low-income country where ballots include candidate photos and where weak institutional checks raise the stakes for selecting innately competent leaders. Estimates provide an example of how voters' use of heuristics need not harm democratic accountability, and can actually enhance it, in cases where these shortcuts identify traits associated with good governance.