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.

摘要：政治学者应如何严谨地评估各类理论的预测能力？诸多已发表的同行评议政治学文章均包含对未来结果的预测，学者们也会在社交媒体及其他公共平台发布相关预测。这类预测的普遍存在，表明学者们意识到借助理论开展预测的价值，但当前多数预测的呈现方式无法支撑对其准确性开展严谨评估。鉴于社会科学领域研究预注册的理念日益普及，本文提出“预测预注册（prediction registration）”方案，供学者发布可证伪、系统化且可验证的基于理论的预测。提升预测性理论检验的严谨性，既能推动关于理论准确性的循环论证式争论取得进展，也能为旨在检验理论预测能力的学者实现“双赢”。采用更严谨的研究路径后，准确的预测将更有力地证明理论的事态预判能力，而预测失误则能揭示可用于校准该理论的有效信息。