Instruments, Randomization, and Learning about Development
Instruments, Randomization, and Learning about Development
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DOI：
10.1257/jel.48.2.424
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发表时间：
2010-06-01
影响因子：
12.6
通讯作者：
Deaton, Angus
中科院分区：
文献类型：
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作者：
Deaton, Angus
目前有很多关于外国援助的有效性和什么样的项目可以产生经济发展的争论。人们怀疑计量经济学分析是否有能力解决这些问题，也怀疑发展机构是否有能力从自己的经验中学习。因此，在发展经济学中越来越多地使用随机对照试验（RCTs）来积累关于什么有效的可靠知识，而不过度依赖有问题的理论或统计方法。当不可能进行随机对照试验时，这些方法的支持者主张通过工具变量（IV）技术或自然实验进行准随机化。我认为，这些应用程序中的许多不太可能恢复对政策或理解有用的数量：两个关键问题是对外生性的误解和对异质性的处理。我从有关援助和增长的文献中举例说明。实际随机化与准随机化面临着类似的问题，尽管有相反的修辞。我认为实验并没有比其他方法产生更可靠的知识的特殊能力，而且实际的实验经常受到实际问题的影响，这些实际问题破坏了任何统计学或认识论优势的主张。我用开发和其他地方的著名实验来说明。与IV方法一样，基于随机对照试验的项目评估，如果没有对潜在机制的理解作为指导，不太可能在理解经济发展方面取得科学进展。我欢迎最近发展实验的趋势，即从评价项目转向评价理论机制。（凝胶c21， f35, o19）
There is currently much debate about the effectiveness of foreign aid and about what kind of projects can engender economic development. There is skepticism about the ability of econometric analysis to resolve these issues or of development agencies to learn from their own experience. In response, there is increasing use in development economics of randomized controlled trials (RCTs) to accumulate credible knowledge of what works, without overreliance on questionable theory or statistical methods. When RCTs are not possible, the proponents of these methods advocate quasi-randomization through instrumental variable (IV) techniques or natural experiments. I argue that many of these applications are unlikely to recover quantities that are useful for policy or understanding: two key issues are the misunderstanding of exogeneity and the handling of heterogeneity. I illustrate from the literature on aid and growth. Actual randomization faces similar problems as does quasi-randomization, notwithstanding rhetoric to the contrary. I argue that experiments have no special ability to produce more credible knowledge than other methods, and that actual experiments are frequently subject to practical problems that undermine any claims to statistical or epistemic superiority. I illustrate using prominent experiments in development and elsewhere. As with IV methods, RCT-based evaluation of projects, without guidance from an understanding of underlying mechanisms, is unlikely to lead to scientific progress in the understanding of economic development. I welcome recent trends in development experimentation away from the evaluation of projects and toward the evaluation of theoretical mechanisms. (JEL C21, F35, O19)