Technical Problems in Social Experimentation: Cost Versus Ease of Analysis
Technical Problems in Social Experimentation: Cost Versus Ease of Analysis
复制标题
社会实验中的技术问题：成本与分析的简易性
DOI：
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发表时间：
1983
期刊：
影响因子：
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通讯作者：
D. Wise
中科院分区：
文献类型：
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作者：
J. Hausman;D. Wise
本文的目的是提出一般准则，我们相信这些准则将增强未来社会实验的实用性，并提出纠正其固有局限性的方法。尽管实验的主要动机是克服结构计量经济学模型的固有局限性，但在许多情况下，实验设计已经颠覆了这一动机。随机对照实验的主要优点常常被丧失。实验分析的主要并发症是由内源样本选择和治疗分配程序引起的，该程序选择实验参与者并将他们分配到对照组与治疗组，部分基于实验旨在测量其反应的变量。我们建议，为了克服这些困难，实验设计的目标应尽可能允许基于简单的方差分析模型进行分析。尽管可以避免内源分层带来的复杂性，但实验存在无法避免的固有局限性。两个主要问题是参与的自我决定和通过消耗而自我选择退出。但我们相信，如果消除内生分层，这些问题可以相对容易地得到纠正。最后，我们建议，作为指导原则，实验应首先对单个或少量治疗效果进行精确估计。
The goal of the paper is to set forth general guidelines that we believe would enhance the usefulness of future social experiments and to suggest ways of correcting for inherent limitations of them. Although the major motivation for an experiment is to overcome the inherent limitations of structural econometric models, in many instances the experimental designs have subverted this motivation. The primary advantages of randomized controlled experiments were often lost. The major complication for the analysis of the experiments was induced by an endogenous sample selection and treatment assignment procedure that selected the experimental participants and assigned them to controlversus treatment groups partly on the basis of the variable whose response the experiments were intended to measure. We propose that to overcome these difficulties, the goal of an experimental design should be as nearly as possible to allow analysis based on a simple analysis of variance model. Although complexities attendant to endogenous stratification can be avoided, there are inherent limitations of the experiments that cannot. Two major ones are self-determination of participation and self-selection out, through attrition.But these problems, we believe, can be corrected for with relative ease if endogenous stratification is eliminated. Finally, we propose that as a guiding principle, the experiments should have as a first priority the precise estimation of a single or a small number of treatment effects.