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摘要翻译：
在本文中，我们讨论了计量经济学的最新发展，我们认为这对政策评估问题的实证研究人员很重要。我们关注三个主要领域，在每个领域我们都强调应用工作的建议。首先，我们讨论了程序评估中识别策略的新研究，特别关注综合控制方法、回归不连续性、外部有效性和回归方法的因果解释。其次，我们讨论了各种形式的补充分析，以使识别策略更加可信。这些包括安慰剂分析以及敏感性和稳健性分析。第三，我们讨论了机器学习方法在因果效应方面的最新进展。这些进展包括调整高维环境中处理单元和控制单元之间差异的方法，以及识别和估计异质处理效果的方法。
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英文标题：
《The State of Applied Econometrics - Causality and Policy Evaluation》
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作者：
Susan Athey and Guido Imbens
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最新提交年份：
2016
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分类信息：
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：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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英文摘要：
In this paper we discuss recent developments in econometrics that we view as important for empirical researchers working on policy evaluation questions. We focus on three main areas, where in each case we highlight recommendations for applied work. First, we discuss new research on identification strategies in program evaluation, with particular focus on synthetic control methods, regression discontinuity, external validity, and the causal interpretation of regression methods. Second, we discuss various forms of supplementary analyses to make the identification strategies more credible. These include placebo analyses as well as sensitivity and robustness analyses. Third, we discuss recent advances in machine learning methods for causal effects. These advances include methods to adjust for differences between treated and control units in high-dimensional settings, and methods for identifying and estimating heterogeneous treatment effects.
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PDF链接：
https://arxiv.org/pdf/1607.00699
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