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Local Projections vs. VARs: Lessons From Thousands of DGPs

Author

Listed:
  • Dake Li
  • Mikkel Plagborg-Møller
  • Christian K. Wolf

Abstract

We conduct a simulation study of Local Projection (LP) and Vector Autoregression (VAR) estimators of structural impulse responses across thousands of data generating processes, designed to mimic the properties of the universe of U.S. macroeconomic data. Our analysis considers various identification schemes and several variants of LP and VAR estimators. A clear bias-variance trade-off emerges: LP estimators have lower bias than VAR estimators but substantially higher variance at intermediate and long horizons. Consequently, unless researchers are overwhelmingly concerned with bias, shrinkage via Bayesian VARs or penalized LPs is attractive.

Suggested Citation

  • Dake Li & Mikkel Plagborg-Møller & Christian K. Wolf, 2022. "Local Projections vs. VARs: Lessons From Thousands of DGPs," NBER Working Papers 30207, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:30207
    Note: EFG ME
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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