SPECIFICATION TESTING IN MODELS WITH MANY INSTRUMENTS
SPECIFICATION TESTING IN MODELS WITH MANY INSTRUMENTS
复制标题
使用多种仪器进行模型规格测试
DOI：
10.1017/s0266466610000307
复制
发表时间：
2008
影响因子：
0.8
通讯作者：
Nikolay Gospodinov
中科院分区：
文献类型：
--
作者：
Stanislav Anatolyev;Nikolay Gospodinov
本文研究了安德森-鲁宾 (AR) 检验和 J 检验的渐近有效性，用于使用多种工具对线性模型中的过度识别限制进行分析。当仪器数量以与样本量相同的速度增加时，我们确定传统的 AR 和 J 检验是渐近错误的。这些测试的某些版本是针对具有中等数量仪器的情况而开发的，在该框架中也被证明是渐近无效的。我们建议修改 AR 和 J 测试，以提供渐近正确的大小。重要的是，校正后的测试对于大量的瞬时条件来说是稳健的，因为它们对于少数和许多仪器都有效。模拟结果说明了所提出的测试的优异性能。
This paper studies the asymptotic validity of the Anderson–Rubin (AR) test and the J test for overidentifying restrictions in linear models with many instruments. When the number of instruments increases at the same rate as the sample size, we establish that the conventional AR and J tests are asymptotically incorrect. Some versions of these tests, which are developed for situations with moderately many instruments, are also shown to be asymptotically invalid in this framework. We propose modifications of the AR and J tests that deliver asymptotically correct sizes. Importantly, the corrected tests are robust to the numerosity of the moment conditions in the sense that they are valid for both few and many instruments. The simulation results illustrate the excellent properties of the proposed tests.