Root-N-Consistent Semiparametric Regression
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One type of semiparametric regression is b8X A u(Z), where b and u(Z) are an unknown slope coefficient vector and function. Estimates of b based on incorrect parametrization of u are generally inconsist ent, whereas consistent nonparametric estimates converge slowly. An e stimate, bC, is constructed by inserting nonpar-ametric regression es timates in the nonlinear orthogonal projection on Z. Under regularity conditions bC is shown to be N1/2-consistent for b and asymptoticall y normal, and a consistent estimate of its limiting covariance matrix is given. The author discusses the identification problem and bC's e fficiency. Extensions to other econometric models are described. Copyright 1988 by The Econometric Society.
嵌套工具变量分析:转换者平均处理效应及可推广性
Instrumental variables (IVs) are widely used to estimate causal effects from non-randomized data. A canonical example is a randomized trial with noncompliance, in which the randomized treatment assignment serves as an IV for the non-ignorable treatment received. Under a monotonicity assumption, a valid IV nonparametrically identifies the average treatment effect among a latent complier subgroup, whose generalizability is often under debate. In many studies, there exist…
前门模型下因果效应的灵活非参数推断
Abstract Evaluating causal treatment effects in observational studies requires addressing confounding. While the back-door criterion enables identification through adjustment for observed covariates, it fails in the presence of unmeasured confounding. The front-door criterion offers an alternative by leveraging variables that fully mediate the treatment effect and are unaffected by unmeasured confounders of the treatment-outcome pair. We develop novel one-step and targeted…
随时间刻画幸存者主层:识别、有效估计与敏感性分析
Longitudinal studies with functional outcomes subject to truncation-by-death frequently report time-indexed survivor average causal effect estimates, defined among individuals who would survive regardless of treatment assignment. Because the survivor stratum can change over time, the resulting effect estimates may pertain to populations with different characteristics. We propose accompanying survivor average causal effect estimates with measures of covariate divergence…
生育、子女性别与父母迁移决策:来自中国的证据
We study how the number and gender of children affect rural-tourban parental migration in China. Exploiting variation from the “1.5- child policy,” which allowed a second birth only if the firstborn was a girl, we separately identify the causal effects of fertility and child gender based on a novel semi-parametric method. Using the 2010 population census, we find that an additional child increases the likelihood of joint parental migration by 12.1 percent, while the presence…
双重差分与合成控制的结合:双重稳健识别和估计
Difference-in-Differences (DiD) and Synthetic Control (SC) are widely used methods for causal inference in panel data, each with distinct strengths and limitations. We propose a novel method for short-panel causal inference that integrates the advantages of both approaches. Our method delivers a doubly robust identification strategy for the average treatment effect on the treated (ATT) under either of two non-nested assumptions: parallel trends or a group-level SC condition.…
整群随机试验中依从效应与网络因果效应的识别和有效估计
Treatment noncompliance is pervasive in infectious disease cluster-randomized trials. Although all individuals within a cluster are assigned the same treatment condition, the treatment uptake status may vary across individuals due to noncompliance. We propose a semiparametric framework to evaluate the individual compliance effect and network assignment effect within principal stratum exhibiting different patterns of noncompliance. The individual compliance effect captures…