Feedback and Learning: The Causal Effects of Reversals on Judicial Decision-Making
利用挪威刑事司法系统中案件随机分配和上诉法院撤销判决的数据，研究发现初审法官在收到撤销判决后会调整未来判决中判处监禁的概率，且反应强度受法官先验信念和信号强度影响，但存在过度反应。
Abstract Do judges respond to reversals of their decisions? Using random assignment of cases across two stages of the criminal justice system in Norway and a novel dataset linking trial court decisions to reversals in appeals courts, we provide causal evidence on feedback effects in judicial decision-making. By exploiting differences in the tendencies of randomly assigned appeal panels to reverse trial court decisions, we show that trial court judges who receive a reversal of a sentence respond by updating the likelihood of imposing a prison sentence in the direction of the reversal in future cases. Consistent with a Bayesian learning model, we find that the responses are stronger for judges with weaker priors and for reversals corresponding to stronger signals. Our estimates, however, also indicate that judges overreact to reversals compared to Bayes’ rule.