Full Citation

Title: Robust estimation with many instruments

Citation Type: Journal Article

Publication Year: 2020

ISBN:

ISSN: 18726895

DOI: 10.1016/j.jeconom.2019.04.040

NSFID:

PMCID:

PMID:

Abstract: Linear instrumental variables models are widely used in empirical work, but often associated with low estimator precision. This paper proposes an estimator that is robust to outliers and shows that the estimator is minimax optimal in a class of estimators that includes the limited maximum likelihood estimator (LIML). Intuitively, this optimal robust estimator combines LIML with Winsorization of the structural residuals and the Winsorization leads to improved precision under thick-tailed error distributions. Consistency and asymptotic normality of the estimator are established under many instruments asymptotics and a consistent variance estimator which allows for asymptotically valid inference is provided.

Url: https://www.sciencedirect.com/science/article/pii/S0304407619301721

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Authors: Sølvsten, Mikkel

Periodical (Full): Journal of Econometrics

Issue: 2

Volume: 214

Pages: 495-512

Data Collections: IPUMS USA

Topics: Other

Countries: