Tests of exogeneity in duration models with censored data
右删失持续时间模型的外生性检验AI 解读 ↓
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AI 根据所提供的论文材料归类：摘要以处理对持续时间的因果效应为背景，利用工具变量检验处理外生性，因此归入因果推断。
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右删失持续时间模型的外生性检验
- 研究问题
- 在持续时间结果受到右删失的非参数非可分模型中，如何借助工具变量检验处理的条件外生性，并处理条件秩本身被删失的问题？
- 方法与思路
- 作者假定模型对误差严格递增，协变量、工具与处理均为分类变量；基于条件秩的独立性构造检验，并推导极限分布与自助临界值。
- 材料陈述的贡献
- 摘要称，在一个可识别性条件下秩独立性与处理外生性等价，并给出秩分布估计的快速收敛结果、模拟及就业培训应用。
- 阅读关注点
- 应核对等价性所需的可识别性条件、工具有效性及删失处理条件，尤其确认快于参数速度的结果具体针对哪个估计对象。
- 阅读边界
- 这是 arXiv 预印本，同行评审与期刊接收均未核实；摘要未完整说明删失条件与检验功效，分类变量设定也限制直接推广。
原文摘要
Consider the setting in which a researcher is interested in the causal effect of a treatment $Z$ on a duration time $T$, which is subject to right censoring. We assume that $T=\varphi(X,Z,U)$, where $X$ is a vector of baseline covariates, $\varphi(X,Z,U)$ is strictly increasing in the error term $U$ for each $(X,Z)$ and $U\sim \mathcal{U}[0,1]$. Therefore, the model is nonparametric and nonseparable. We propose nonparametric tests for the hypothesis that $Z$ is exogenous, meaning that $Z$ is independent of $U$ given $X$. The test statistics rely on an instrumental variable $W$ that is independent of $U$ given $X$. We assume that $X,W$ and $Z$ are all categorical. Test statistics are constructed for the hypothesis that the conditional rank $V_T= F_{T \mid X,Z}(T \mid X,Z)$ is independent of $(X,W)$ jointly. Under an identifiability condition on $\varphi$, this hypothesis is equivalent to $Z$ being exogenous. However, note that $V_T$ is censored by $V_C =F_{T \mid X,Z}(C \mid X,Z)$, which complicates the construction of the test statistics significantly. We derive the limiting distributions of the proposed tests and prove that our estimator of the distribution of $V_T$ converges to the uniform distribution at a rate faster than the usual parametric $n^{-1/2}$-rate. We demonstrate that the test statistics and bootstrap approximations for the critical values have a good finite sample performance in various Monte Carlo settings. Finally, we illustrate the tests with an empirical application to the National Job Training Partnership Act (JTPA) Study.