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arXiv · 2004.12445

Inference with Many Weak Instruments

Anna Mikusheva·Liyang Sun
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Abstract

We develop a concept of weak identification in linear IV models in which the number of instruments can grow at the same rate or slower than the sample size. We propose a jackknifed version of the classical weak identification-robust Anderson-Rubin (AR) test statistic. Large-sample inference based on the jackknifed AR is valid under heteroscedasticity and weak identification. The feasible version of this statistic uses a novel variance estimator. The test has uniformly correct size and good power properties. We also develop a pre-test for weak identification that is related to the size property of a Wald test based on the Jackknife Instrumental Variable Estimator (JIVE). This new pre-test is valid under heteroscedasticity and with many instruments.

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Anna Mikusheva, Liyang Sun. 2020-04-26. Inference with Many Weak Instruments. https://arxiv.org/abs/2004.12445

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