论文标题
我们什么时候应该（不）将线性IV估计为迟到？
When Should We (Not) Interpret Linear IV Estimands as LATE?
论文作者
论文摘要
在本文中，我对线性仪器变量（IV）的解释估计为有条件的局部平均治疗效果（LATE）的加权平均值。我关注的是，由于隐式同质性限制对仪器的影响，因此需要识别额外的协变量来识别识别和第一阶段回归。我表明，某些条件性的重量是负面的，而IV估计不再可以解释为弱版本单调性下的因果效应，即何时有合适的情况，但在某些协方差值和辩护人的情况下没有辩解，但在其他地方没有任何符合条件。负重的问题在Angrist and Imbens（1995）的相互作用规范中消失了，该规范避免了指定错误，并且在应用工作中似乎没有任何用途。我在申请中说明了我对审前拘留对病例结果的因果影响的发现。在这种情况下，我拒绝了更强的单调性，证明了相互作用的仪器足够强大，可以使用Jackknife方法进行一致的估算，并且根据是否使用了相互作用的仪器，它们在经济和统计学上具有不同的估计。
In this paper I revisit the interpretation of the linear instrumental variables (IV) estimand as a weighted average of conditional local average treatment effects (LATEs). I focus on a situation in which additional covariates are required for identification while the reduced-form and first-stage regressions may be misspecified due to an implicit homogeneity restriction on the effects of the instrument. I show that the weights on some conditional LATEs are negative and the IV estimand is no longer interpretable as a causal effect under a weaker version of monotonicity, i.e. when there are compliers but no defiers at some covariate values and defiers but no compliers elsewhere. The problem of negative weights disappears in the interacted specification of Angrist and Imbens (1995), which avoids misspecification and seems to be underused in applied work. I illustrate my findings in an application to the causal effects of pretrial detention on case outcomes. In this setting, I reject the stronger version of monotonicity, demonstrate that the interacted instruments are sufficiently strong for consistent estimation using the jackknife methodology, and present several estimates that are economically and statistically different, depending on whether the interacted instruments are used.
