发帖
雷达卡
摘要翻译：
工具变量(IV)估计在分析处理条件时存在选择偏差。朱迪亚·珀尔对工具变量的早期图形定义明确禁止对治疗进行条件限制。尽管如此，这种做法仍然很普遍。在本文中，我们导出了在一系列数据生成模型和各种选择诱导过程中IV选择偏差的精确解析表达式。对于线性模型，我们给出了四组结果。首先，IV选择偏差取决于条件处理程序（协变量调整与样本截断）。其次，协变量调整导致的IV选择偏差是样本截断导致的IV选择偏差的极限情况。第三，在一定的模型中，选择条件下的IV和OLS估计量对大样本中的真实因果效应进行了约束。第四，我们描述了尽管在治疗上进行了选择，但静脉注射仍然优于OLS的情况。这些结果拓宽了IV选择偏差的概念，超越了样本截断，用精确的分析公式取代了先前的模拟结果，并使正式的灵敏度分析成为可能。
---
英文标题：
《Instrumental Variables with Treatment-Induced Selection: Exact Bias
Results》
---
作者：
Felix Elwert and Elan Segarra
---
最新提交年份：
2020
---
分类信息：
一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
--
一级分类：Statistics 统计学
二级分类：Methodology 方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
--
---
英文摘要：
Instrumental variables (IV) estimation suffers selection bias when the analysis conditions on the treatment. Judea Pearl's early graphical definition of instrumental variables explicitly prohibited conditioning on the treatment. Nonetheless, the practice remains common. In this paper, we derive exact analytic expressions for IV selection bias across a range of data-generating models, and for various selection-inducing procedures. We present four sets of results for linear models. First, IV selection bias depends on the conditioning procedure (covariate adjustment vs. sample truncation). Second, IV selection bias due to covariate adjustment is the limiting case of IV selection bias due to sample truncation. Third, in certain models, the IV and OLS estimators under selection bound the true causal effect in large samples. Fourth, we characterize situations where IV remains preferred to OLS despite selection on the treatment. These results broaden the notion of IV selection bias beyond sample truncation, replace prior simulation findings with exact analytic formulas, and enable formal sensitivity analyses.
---
PDF链接：
https://arxiv.org/pdf/2005.09583
京公网安备 11010802022788号
