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Local Projection Inference in High Dimensions

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  • Robert Adamek
  • Stephan Smeekes
  • Ines Wilms

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.

Suggested Citation

  • Robert Adamek & Stephan Smeekes & Ines Wilms, 2022. "Local Projection Inference in High Dimensions," Papers 2209.03218, arXiv.org, revised Apr 2024.
    • Handle: RePEc:arx:papers:2209.03218
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