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摘要翻译：
本文提出了一种在网络干扰的非实验环境中得出因果推断的方法。具体来说，我们开发了一个广义的基于倾向评分的估计器，它允许我们估计通过网络的加权和有向边缘传播的连续治疗的直接和溢出效应。为了展示这一方法，我们研究了溢出效应是否以及如何影响农业市场政策干预的最佳水平。我们的结果表明，在这种背景下，忽视干预可能会导致评估政策有效性时的向下偏差。
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英文标题：
《Causal Inference on Networks under Continuous Treatment Interference》
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作者：
Davide Del Prete, Laura Forastiere, Valerio Leone Sciabolazza
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最新提交年份：
2020
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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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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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英文摘要：
This paper presents a methodology to draw causal inference in a non-experimental setting subject to network interference. Specifically, we develop a generalized propensity score-based estimator that allows us to estimate both direct and spillover effects of a continuous treatment, which spreads through weighted and directed edges of a network. To showcase this methodology, we investigate whether and how spillover effects shape the optimal level of policy interventions in agricultural markets. Our results show that, in this context, neglecting interference may lead to a downward bias when assessing policy effectiveness.
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PDF链接：
https://arxiv.org/pdf/2004.13459
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