Review of Economic Studies Vol. 89 No. 5 2022
Inference with Many Weak Instruments
Abstract
We develop a concept of weak identification in linear instrumental variable 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. This new pre-test is valid under heteroscedasticity and with many instruments.
- DOI
- 10.1093/restud/rdab097
- Volume
- 89
- Issue
- 5
- Pages
- 2663-2686
- Language
- en
- Sources
- bibtex:phds-export.bib crossref openalex