Estimation and Inference of Impulse Responses by Local Projections
2005/02/01 by Òscar Jordà · 4,536 citations
Economics, Econometrics and Finance · Mathematics · #Artificial intelligence #Computer science #Econometrics #Economics #Economics of Agriculture and Food Markets #Impulse response #Inference #Machine learning #Market Dynamics and Volatility #Mathematics #Monetary Policy and Economic Impact #Monte Carlo method #Multivariate statistics #Point estimation #Regression #Statistical inference #Statistics
paper · doi:10.1257/0002828053828518
published in American Economic Review 95(1), 161-182 (American Economic Association)
openalex publication_date 2005/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Abstract
This paper introduces methods to compute impulse responses without specification and estimation of the underlying multivariate dynamic system. The central idea consists in estimating local projections at each period of interest rather than extrapolating into increasingly distant horizons from a given model, as it is done with vector autoregressions (VAR). The advantages of local projections are numerous: (1) they can be estimated by simple regression techniques with standard regression packages; (2) they are more robust to misspecification; (3) joint or point-wise analytic inference is simple; and (4) they easily accommodate experimentation with highly nonlinear and flexible specifications that may be impractical in a multivariate context. Therefore, these methods are a natural alternative to estimating impulse responses from VARs. Monte Carlo evidence and an application to a simple, closed-economy, new-Keynesian model clarify these numerous advantages.
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