Impulse Response Estimation by Smooth Local Projections

By Regis Barnichon, C. Brownlees. Review of Economics and Statistics, 2019

203 citations recorded by the source corpus.

Abstract Local projections (LP) is a popular methodology for the estimation of impulse responses (IR). Compared to the traditional VAR approach, LP allow for more flexible IR estimation by imposing weaker assumptions on the dynamics of the data. The nonparametric nature of LP comes at an efficiency cost, and in practice, the LP estimator may suffer from excessive variability. In this work, we propose an IR estimation methodology based on B-spline smoothing called smooth local projections (SLP). The SLP approach preserves the flexibility of standard LP, can substantially increase precision, and is straightforward to implement. A simulation study shows that SLP can deliver substantial gains in IR estimation over LP. We illustrate our technique by studying the effects of monetary shocks where we highlight how SLP can easily incorporate commonly employed structural identification strategies.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/1740f45a7a5c2878bf1d146e05081c823bc8105b

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Citations in the corpus

Identification and Estimation of Dynamic Causal Effects in Macroeconomics Using External Instruments (2018, background): “Barnichon and Brownlees (2016) and Plagborg-Møller (2016a) use smoothness priors to shrink the IRFs across horizons.”
Local Projections vs. VARs: Lessons From Thousands of DGPs (2021, methodology): “The Barnichon & Brownlees (2019) estimator lowers the variance of LP by exploiting a prior belief in smoothness of the impulse response function across horizons.”