Journal article
Robust inference in structural vector autoregressions with long-run restrictions
- Abstract:
- Long-run restrictions are a very popular method for identifying structural vector autoregressions, but they suffer from weak identification when the data is very persistent, i.e., when the highest autoregressive roots are near unity. Near unit roots introduce additional nuisance parameters and make standard weak-instrument-robust methods of inference inapplicable. We develop a method of inference that is robust to both weak identification and strong persistence. The method is based on a combination of the Anderson-Rubin test with instruments derived by filtering potentially nonstationary variables to make them near stationary using the IVX instrumentation method of Magdalinos and Phillips (2009). We apply our method to obtain robust confidence bands on impulse responses in two leading applications in the literature.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, 1.1MB, Terms of use)
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- Publisher copy:
- 10.1017/S0266466619000045
Authors
- Publisher:
- Cambridge University Press
- Journal:
- Econometric Theory More from this journal
- Volume:
- 36
- Issue:
- 1
- Pages:
- 86-121
- Publication date:
- 2019-03-05
- DOI:
- EISSN:
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1469-4360
- ISSN:
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0266-4666
- Language:
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English
- Keywords:
- Pubs id:
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1084357
- Local pid:
-
pubs:1084357
- Deposit date:
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2020-06-01
Terms of use
- Copyright holder:
- Cambridge University Press
- Copyright date:
- 2020
- Rights statement:
- © Cambridge University Press 2019. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Licence:
- CC Attribution (CC BY)
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