Local projection inference in high dimensions

Robert Adamek, Stephan Smeekes, Ines Wilms

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

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.

Original languageEnglish
JournalEconometrics Journal
Volume27
Issue3
Pages (from-to)323-342
Number of pages20
ISSN1368-4221
DOIs
Publication statusPublished - 1 Sept 2024

Keywords

  • high-dimensional data
  • honest inference
  • impulse response analysis
  • lasso
  • Local projections

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