Quantitative Economics
Journal Of The Econometric Society
Edited by: Stéphane Bonhomme • Print ISSN: 1759-7323 • Online ISSN: 1759-7331
Quantitative Economics: May, 2024, Volume 15, Issue 2
Locally Robust Inference for Non-Gaussian SVAR models
https://doi.org/10.3982/QE2274
p. 523-570
Lukas Hoesch, Adam Lee, Geert Mesters
All parameters in structural vector autoregressive (SVAR) models are locally identified when the structural shocks are independent and follow non‐Gaussian distributions. Unfortunately, standard inference methods that exploit such features of the data for identification fail to yield correct coverage for structural functions of the model parameters when deviations from Gaussianity are small. To this extent, we propose a locally robust semiparametric approach to conduct hypothesis tests and construct confidence sets for structural functions in SVAR models. The methodology fully exploits non‐Gaussianity when it is present, but yields correct size/coverage for local‐to‐Gaussian densities. Empirically, we revisit two macroeconomic SVAR studies where we document mixed results. For the oil price model of Kilian and Murphy (2012), we find that non‐Gaussianity can robustly identify reasonable confidence sets, whereas for the labor supply–demand model of Baumeister and Hamilton (2015) this is not the case. Moreover, these exercises highlight the importance of using weak identification robust methods to assess estimation uncertainty when using non‐Gaussianity for identification.
Full Content: Print
Supplemental Material
Supplement to "Locally Robust Inference for Non-Gaussian SVAR models"
Lukas Hoesch, Adam Lee, and Geert Mesters
The replication package for this paper is available at https://doi.org/10.5281/zenodo.10539210. The Journal checked the data and codes included in the package for their ability to reproduce the results in the paper and approved online appendices.Supplement to "Locally Robust Inference for Non-Gaussian SVAR models"
Lukas Hoesch, Adam Lee and Geert Mesters
In this supplementary material we provide the following additional results.S1: Choice for the parametrization
S2: Technical details for the main proofs
S3: Some technical tools
Journal News
March 5, 2024
Announcing the New Journal Editors
The terms of the Editors of the Econometric Society's three journals end June 30, 2025. We are pleased to announce the incoming Editors and to thank the outgoing Editors for their excellent and continuing service.
Econometrica: Since 2019, Guido Imbens has served as the 14th Editor of Econometrica. On July 1, 2025, Marina Halac will become the Editor.
Quantitative Economics: Stéphane Bonhomme has been the Editor of Quantitative Economics since 2021. His successor will be Bernard Salanié.
Theoretical Economics: The Editor of Theoretical Economics since 2021 has been Simon Board. Taking over for him in July 2025 will be Federico Echenique.
Guido, Stéphane, and Simon have been outstanding Editors. We are grateful to them for the work they have done and will continue to do, and we look forward to further congratulating them next year. We believe Marina, Bernard, and Federico will be outstanding successors and we thank them in advance for their service.
Finally, we are grateful to Larry Samuelson for chairing all three search committees, and we thank the search committee members for their hard and fruitful work:
Econometrica: Christian Dustmann, Lars Hansen, Alessandro Lizzeri, George Mailath, Ariel Pakes, Helene Rey, and Elie Tamer.
QE: Kate Ho, Michael Keane, Felix Kubler, Whitney Newey, and Frank Schorfheide.
TE: Jeff Ely, Johannes Horner, Gilat Levy, Meg Meyer, and Ran Spiegler.
