For variables with a term structure, the standard difference-in-differences (DiD) model is predisposed toward misspecification, even under random assignment, because of heterogeneity over the maturity spectrum and imperfect matching between treated and control units. Estimated treatment effects that are false, biased, or hard to interpret become a concern. Neither unit fixed effects nor standard term-structure controls resolve the problem. Solutions that overcome imperfect matching involve estimating the term structure of hypothesized treatment, which is also what is economically interesting (regardless of matching efficiency). These issues are not unique to DiD analysis, but are generic to group-assignment settings.

中文翻译：

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存在项结构时的稳健双重差分分析

对于具有项结构的变量，标准双重差分 （DiD） 模型容易出现错误指定，即使在随机分配下也是如此，因为成熟度谱的异质性以及处理单元和控制单元之间的不完美匹配。估计的治疗效果是错误的、偏倚的或难以解释的，成为一个问题。单位固定效应和标准项结构控制都无法解决问题。克服不完全匹配的解决方案涉及估计假设治疗的项结构，这也是经济上有趣的地方（无论匹配效率如何）。这些问题并非 DiD 分析所独有，而是组分配设置的通用问题。