摘要翻译：
本文研究了当数据由单个大网络组成时，具有社会交互作用的离散选择模型的推理问题。我们为空间和网络HAC方差估计在实际工作中的使用提供了理论依据，后者是用网络路径距离代替空间距离构造的。为此，我们在一大类社会互动模型中证明了网络矩的中心极限定理。结果适用于网络上的离散博弈和社会互动通过滞后因变量进入的动态模型。我们在一个经验应用和模拟研究中说明了我们的结果。
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英文标题：
《Inference in Models of Discrete Choice with Social Interactions Using
  Network Data》
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作者：
Michael P. Leung
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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：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 studies inference in models of discrete choice with social interactions when the data consists of a single large network. We provide theoretical justification for the use of spatial and network HAC variance estimators in applied work, the latter constructed by using network path distance in place of spatial distance. Toward this end, we prove new central limit theorems for network moments in a large class of social interactions models. The results are applicable to discrete games on networks and dynamic models where social interactions enter through lagged dependent variables. We illustrate our results in an empirical application and simulation study.
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PDF链接：
https://arxiv.org/pdf/1911.07106