2021/04/01 by Dake Li, Mikkel Plagborg‐Møller, Li, Dake +3 · 2 citations
Economics, Econometrics and Finance · #Econometrics (econ.EM) #Economic Policies and Impacts #FOS: Economics and business #Market Dynamics and Volatility #Monetary Policy and Economic Impact
paper · pdf · doi:10.48550/arxiv.2104.00655
openalex publication_date 2021/04/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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, employing bias correction, shrinkage, or model averaging. A clear bias-variance trade-off emerges: LP estimators have lower bias than VAR estimators, but they also have substantially higher variance at intermediate and long horizons. Bias-corrected LP is the preferred method if and only if the researcher overwhelmingly prioritizes bias. For researchers who also care about precision, VAR methods are the most attractive -- Bayesian VARs at short and long horizons, and least-squares VARs at intermediate and long horizons.