This paper provides a general framework for testing instrument validity in heterogeneous causal effect models. The generalization includes the cases where the treatment can be multivalued ordered or unordered. Based on a series of testable implications, we propose a nonparametric test which is proved to be asymptotically size controlled and consistent. Compared to the tests in the literature, our test can be applied in more general settings and may achieve power improvement. Refutation of instrument validity by the test helps detect invalid instruments that may yield implausible results on causal effects. Evidence that the test performs well on finite samples is provided via simulations. We revisit the empirical study on return to schooling to demonstrate application of the proposed test in practice. An extended continuous mapping theorem and an extended delta method, which may be of independent interest, are provided to establish the asymptotic distribution of the test statistic under null.
翻译:本文为各种因果效应模型的测试仪器有效性提供了一个总体框架。一般情况包括处理方法可以多价定购或无顺序定购的情况。根据一系列可测试的影响,我们建议进行非参数测试,该测试被证明是非瞬时性大小的控制和一致的。与文献中的测试相比,我们的测试可以在更一般的环境中应用,并可能实现功率的提高。测试对仪器有效性的否定有助于检测可能产生不可信的因果关系结果的无效仪器。测试在有限样品上表现良好的证据是通过模拟提供的。我们重新审视关于返回学校的经验研究,以证明拟议测试的实际应用情况。提供了一种扩展的连续绘图标语和扩展的三角形方法,可能具有独立的兴趣,以确定无效测试统计的无症状分布。