Local Projection Inference in High Dimensions

Robert Adamek; Stephan Smeekes; Ines Wilms

doi:10.1093/ectj/utae012

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arXiv · 2209.03218

Local Projection Inference in High Dimensions

Robert Adamek·Stephan Smeekes·Ines Wilms

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Abstract

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.

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BibTeX RIS

Robert Adamek, Stephan Smeekes, Ines Wilms. 2022-09-07. Local Projection Inference in High Dimensions. https://doi.org/10.1093/ectj%2Futae012

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