Three's a crowd: Identification challenges in the triple difference model with spillover effects
三者成群:存在溢出效应时三重差分模型的识别挑战
The paper studies identification in triple-difference designs when spillover effects contaminate one or more control groups. We show that, under conventional identifying assumptions, the triple-difference model fails to identify both the treatment effect and the spillover effect under such interference. To overcome this limitation, we propose an alternative specification, the double-triple-difference model, and explicitly formalize identifying assumptions and spillover…