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Cited by 437

The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.

Local Projection Inference Is Simpler and More Robust Than You Think

Open access
Montiel Olea, José Luis, Plagborg-Møller, Mikkel·2021·Econometrica
DOI 10.3982/ecta18756
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Abstract

Applied macroeconomists often compute confidence intervals for impulse responses using local projections, that is, direct linear regressions of future outcomes on current covariates. This paper proves that local projection inference robustly handles two issues that commonly arise in applications: highly persistent data and the estimation of impulse responses at long horizons. We consider local projections that control for lags of the variables in the regression. We show that lag‐augmented local projections with normal critical values are asymptotically valid uniformly over (i) both stationary and non‐stationary data, and also over (ii) a wide range of response horizons. Moreover, lag augmentation obviates the need to correct standard errors for serial correlation in the regression residuals. Hence, local projection inference is arguably both simpler than previously thought and more robust than standard autoregressive inference, whose validity is known to depend sensitively on the persistence of the data and on the length of the horizon.

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Metadata

Authors
Montiel Olea, J. L., & Plagborg-Møller, M.
Venue
Econometrica
Publisher
The Econometric Society
Published
2021
Volume
89
Issue
4
Pages
1789-1823
ISSN
0012-9682 (ISSN-L)
DOI
10.3982/ecta18756
OpenAlex
W3046044289
Cited by
437
References
40
FWCI
92.55
Type
journal article
Language
en
Open access
green

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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