Local projection inference in high dimensions

Summary In this paper, we estimate impulse responses by local projections in high-dimensional settings. We use the desparsified (de-biased) lasso to estimate the high-dimensional local projections, while leaving the impulse response parameter of interest unpenalized. We establish the uniform asympto...

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Bibliographic Details
Published in:The econometrics journal 2024-10, Vol.27 (3), p.323-342
Main Authors: Adamek, Robert, Smeekes, Stephan, Wilms, Ines
Format: Article
Language:English
Subjects:
Government spending
Monetary policy
Normality
Projections
Simulation
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Summary:Summary In this paper, we estimate impulse responses by local projections in high-dimensional settings. We use the desparsified (de-biased) lasso to estimate the high-dimensional local projections, while leaving the impulse response parameter of interest unpenalized. We establish the uniform asymptotic normality of the proposed estimator under general conditions. Finally, we demonstrate small sample performance through a simulation study and consider two canonical applications in macroeconomic research on monetary policy and government spending.
ISSN:1368-4221
1368-423X
DOI:10.1093/ectj/utae012