Omitted Variable Bias in Interacted Models: A Cautionary Tale
指出，在经济学研究中，使用交互项分析处理效应异质性时，常因遗漏可用变量而产生偏误。基于对《美国经济评论》17篇论文205个估计的复制，约60%的论文因遗漏变量导致多数估计变化超过100%。
Abstract We highlight that analyses using interaction terms to study treatment effect heterogeneity are susceptible to a form of omitted variable bias that is often overlooked in economics. Unlike most instances of omitted variable bias, the omitted variables in this case are available to the researcher but were not included in the model. We demonstrate that this exclusion matters based on a replication of 205 estimates across seventeen papers published in the American Economic Review over a five-year period. For approximately 60% of these papers, failing to account for the omitted variables changes the majority of estimates by more than 100%.