Identification of treatment response with social interactions
Identification of treatment response with social interactions
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DOI：
10.1111/j.1368-423x.2012.00368.x
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发表时间：
2013-01-01
影响因子：
1.9
通讯作者：
Manski, Charles F.
中科院分区：
文献类型：
--
作者：
Manski, Charles F.
本文研究识别潜在的结果分布时，治疗反应可能有社会相互作用。定义一个人的治疗反应是一个函数的整个向量的治疗收到的人口，我研究识别时，非参数形状的限制和分布假设放置在响应函数。早期的一个关键结果是，个体化治疗反应的传统假设是恒定治疗反应（CTR）假设的广泛类别中的一个极，另一个极是不受限制的相互作用。重要的非极性情况是参考群体内的相互作用和匿名相互作用。我首先在假设CTR下单独研究识别。然后，我加强这个假设半单调响应。接下来，我将讨论这些假设从内生相互作用模型的推导。最后，我将联合收割机假设CTR与已实现的有效治疗的潜在结果的统计独立性相结合。这些发现既扩展又界定了随机实验的经典分析。
This paper studies identification of potential outcome distributions when treatment response may have social interactions. Defining a person's treatment response to be a function of the entire vector of treatments received by the population, I study identification when non-parametric shape restrictions and distributional assumptions are placed on response functions. An early key result is that the traditional assumption of individualistic treatment response is a polar case within the broad class of constant treatment response (CTR) assumptions, the other pole being unrestricted interactions. Important non-polar cases are interactions within reference groups and anonymous interactions. I first study identification under Assumption CTR alone. I then strengthen this Assumption to semi-monotone response. I next discuss derivation of these assumptions from models of endogenous interactions. Finally, I combine Assumption CTR with statistical independence of potential outcomes from realized effective treatments. The findings both extend and delimit the classical analysis of randomized experiments.