Replication Data for: Registering Theory-based Predictions in Political Science

Abstract: How can political scientists rigorously evaluate the predictive power of theories? Many peer-reviewed political science articles include predictions about future outcomes, and scholars make predictions on social media and other public forums. The prevalence of predictions suggests that scholars recognize the utility of leveraging theories for this purpose, but the predictions often are not made in a manner that allows for rigorously evaluating their accuracy. Building on the increasing popularity of study preregistration in the social sciences, this article proposes “prediction registration” as a means for scholars to publish falsifiable, systematic, and verifiable theory-based predictions. Increasing the rigor of predictive theory testing can advance often-circular debates about accuracy and presents a “win-win” for scholars who aim to test theories’ predictive power. With a more rigorous approach, correct predictions would better demonstrate a theory’s ability to forecast outcomes, and missed predictions would reveal information that can be used to calibrate the theory.