网络干扰与不依从随机化实验分析
Analysis of Randomized Experiments with Network Interference and Noncompliance
摘要：
随机实验已经成为经济学中的标准工具。在分析随机化实验时，传统方法基于稳定单位治疗值（SUTVA：\cite{rubin}）假设，该假设表明个体之间不存在干扰。然而，由于社会互动、一般均衡和/或外部性效应，SUTVA假设在许多应用中不成立。虽然在放宽SUTVA假设方面取得了很大进展，但大多数文献仅考虑了对治疗分配具有完美依从性的设置。然而，在实践中，当实际接受的治疗与分配的治疗不同时，不依从的情况经常发生。本文研究了网络干扰和不服从随机实验中的因果效应。溢出允许发生在治疗选择阶段和结果实现阶段。特别是，我们明确的治疗选择代理作为一个不完全信息的二元博弈模型，由此产生的均衡治疗选择概率影响结果的利益。通过随机系数模型进一步表征结局，以允许因果效应中的一般未观察到的异质性。在定义了我们感兴趣的因果参数后，我们提出了一个简单的控制函数估计器，并推导出它在大网络渐近下的渐近性质。我们将我们的方法应用到\cite{dupas}的随机补贴计划中，我们发现了短期和长期采用经杀虫剂处理的蚊帐的溢出效应的证据。最后，我们通过分析反事实补贴政策的影响来说明我们的方法的有用性。
英文摘要：
Randomized experiments have become a standard tool in economics. In analyzing randomized experiments, the traditional approach has been based on the Stable Unit Treatment Value (SUTVA: \cite{rubin}) assumption which dictates that there is no interference between individuals. However, the SUTVA assumption fails to hold in many applications due to social interaction, general equilibrium, and/or externality effects. While much progress has been made in relaxing the SUTVA assumption, most of this literature has only considered a setting with perfect compliance to treatment assignment. In practice, however, noncompliance occurs frequently where the actual treatment receipt is different from the assignment to the treatment. In this paper, we study causal effects in randomized experiments with network interference and noncompliance. Spillovers are allowed to occur at both treatment choice stage and outcome realization stage. In particular, we explicitly model treatment choices of agents as a binary game of incomplete information where resulting equilibrium treatment choice probabilities affect outcomes of interest. Outcomes are further characterized by a random coefficient model to allow for general unobserved heterogeneity in the causal effects. After defining our causal parameters of interest, we propose a simple control function estimator and derive its asymptotic properties under large-network asymptotics. We apply our methods to the randomized subsidy program of \cite{dupas} where we find evidence of spillover effects on both short-run and long-run adoption of insecticide-treated bed nets. Finally, we illustrate the usefulness of our methods by analyzing the impact of counterfactual subsidy policies.
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