摘要翻译：
本文提出了一种具有噪声测量混杂物的治疗效应模型的一般因果推断方法。其关键特征是大量的噪声测量通过一个未知的、可能是非线性的因子结构与潜在的混杂联系在一起。主要构造块是一个结合了$k$-最近邻匹配和主成分分析的局部主子空间逼近过程。基于双鲁棒得分函数构造了许多因果参数的估计，包括平均治疗效果和反事实分布。建立了这些估计量的大样本性质，只需要相对温和的主子空间逼近条件。通过实证研究政治关系对金融公司股票收益的影响，以及蒙特卡罗实验，说明了这一结果。关于一般局部主子空间近似方法的主要技术和方法学结果可能是独立感兴趣的。
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英文标题：
《Causal Inference in Possibly Nonlinear Factor Models》
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作者：
Yingjie Feng
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最新提交年份：
2021
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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。
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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
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一级分类：Statistics        统计学
二级分类：Machine Learning        机器学习
分类描述：Covers machine learning papers (supervised, unsupervised, semi-supervised learning, graphical models, reinforcement learning, bandits, high dimensional inference, etc.) with a statistical or theoretical grounding
覆盖机器学习论文（监督，无监督，半监督学习，图形模型，强化学习，强盗，高维推理等）与统计或理论基础
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英文摘要：
  This paper develops a general causal inference method for treatment effects models with noisily measured confounders. The key feature is that a large set of noisy measurements are linked with the underlying latent confounders through an unknown, possibly nonlinear factor structure. The main building block is a local principal subspace approximation procedure that combines $K$-nearest neighbors matching and principal component analysis. Estimators of many causal parameters, including average treatment effects and counterfactual distributions, are constructed based on doubly-robust score functions. Large-sample properties of these estimators are established, which only require relatively mild conditions on the principal subspace approximation. The results are illustrated with an empirical application studying the effect of political connections on stock returns of financial firms, and a Monte Carlo experiment. The main technical and methodological results regarding the general local principal subspace approximation method may be of independent interest.
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PDF链接：
https://arxiv.org/pdf/2008.13651