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Local Projections vs. VARs: Lessons From Thousands of DGPs / Dake Li, Mikkel Plagborg-Møller, Christian K. Wolf.

NBER Working papers Available online

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Format:
Book
Author/Creator:
Li, Dake.
Contributor:
National Bureau of Economic Research.
Plagborg-Møller, Mikkel.
Wolf, Christian K.
Series:
Working Paper Series (National Bureau of Economic Research) no. w30207.
NBER working paper series no. w30207
Language:
English
Physical Description:
1 online resource: illustrations (black and white);
Place of Publication:
Cambridge, Mass. National Bureau of Economic Research 2022.
Summary:
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.
Notes:
Print version record
July 2022.

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