摘要翻译：
本文建立了一个非参数模型，它描述了结果序列和治疗选择如何以动态的方式相互影响。在这种情况下，我们感兴趣的是确定每个时期的个体的平均结果，有一个特定的治疗序列被分配。这个量的确定允许我们确定平均治疗效果(ATE's)和过渡的ATE's，以及最佳治疗方案，即最大化平均潜在结果的（加权）和，可能减少治疗费用的方案。本文的主要贡献在于通过引入一个灵活的内源治疗序列选择理论框架，放宽了生物统计学文献中广泛使用的序列随机化假设。我们表明，感兴趣的参数是在每个阶段的双向排除限制下识别的，即，将工具排除在结果决定过程之外，将其他外生变量排除在治疗选择过程之外。我们还考虑了在后一个变量不可用的情况下的部分辨识。最后，我们将我们的结果扩展到一个不是每个时期都出现治疗的环境中。
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英文标题：
《Identification in Nonparametric Models for Dynamic Treatment Effects》
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作者：
Sukjin Han
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最新提交年份：
2019
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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：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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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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英文摘要：
  This paper develops a nonparametric model that represents how sequences of outcomes and treatment choices influence one another in a dynamic manner. In this setting, we are interested in identifying the average outcome for individuals in each period, had a particular treatment sequence been assigned. The identification of this quantity allows us to identify the average treatment effects (ATE's) and the ATE's on transitions, as well as the optimal treatment regimes, namely, the regimes that maximize the (weighted) sum of the average potential outcomes, possibly less the cost of the treatments. The main contribution of this paper is to relax the sequential randomization assumption widely used in the biostatistics literature by introducing a flexible choice-theoretic framework for a sequence of endogenous treatments. We show that the parameters of interest are identified under each period's two-way exclusion restriction, i.e., with instruments excluded from the outcome-determining process and other exogenous variables excluded from the treatment-selection process. We also consider partial identification in the case where the latter variables are not available. Lastly, we extend our results to a setting where treatments do not appear in every period.
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PDF链接：
https://arxiv.org/pdf/1805.09397