Causal Interaction and External Validity: Obstacles to the Policy Relevance of Randomized Evaluations
从因果交互角度分析随机实验结论难以推广到其他人群或环境的问题，指出当前方法存在不一致性，并强调需要更多关于交互因素的知识才能进行可信的外推。
The ability to generalize effects estimated from randomized experiments is critical for their relevance to policy. Framing that problem in terms of causal interaction reveals the extent to which the literature to date has failed to adequately address external validity. An analogy with matching estimators illustrates the current inconsistency in approaches to estimating causal relationships and generalizing these estimates to other populations and contexts. Contrary to some claims, atheoretic replication is not a plausible solution. Better knowledge of, and more information on, interacting factors is required for credible, formal extrapolation. In the absence of that, modesty is recommended.