Inference with Many Weak Instruments

Anna Mikusheva and Liyang Sun

The Review of Economic Studies, 2022, vol. 89, issue 5, 2663-2686

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.

Keywords: Instrumental variables; Weak identification; Dimensionality asymptotics; C12; C36; C55 (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (19)

Downloads: (external link)
http://hdl.handle.net/10.1093/restud/rdab097 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Inference with Many Weak Instruments (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:restud:v:89:y:2022:i:5:p:2663-2686.

Access Statistics for this article

The Review of Economic Studies is currently edited by Thomas Chaney, Xavier d’Haultfoeuille, Andrea Galeotti, Bård Harstad, Nir Jaimovich, Katrine Loken, Elias Papaioannou, Vincent Sterk and Noam Yuchtman

More articles in The Review of Economic Studies from Review of Economic Studies Ltd
Bibliographic data for series maintained by Oxford University Press ().