2010
DOI: 10.1198/jbes.2009.08116
|View full text |Cite
|
Sign up to set email alerts
|

Inference in Nearly Nonstationary SVAR Models With Long-Run Identifying Restrictions

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

1
31
0

Year Published

2011
2011
2022
2022

Publication Types

Select...
4
2

Relationship

1
5

Authors

Journals

citations
Cited by 30 publications
(32 citation statements)
references
References 18 publications
1
31
0
Order By: Relevance
“…The estimator from the levels specification exhibits a modest bias that arises from the biased estimation of the largest root of hours and a very large sample uncertainty (Gospodinov, 2006). The estimator from the specification with HP filtered labour productivity growth performs similarly to the differenced estimator although it is slightly biased and more dispersed.…”
Section: Monte Carlo Experimentsmentioning
confidence: 81%
See 4 more Smart Citations
“…The estimator from the levels specification exhibits a modest bias that arises from the biased estimation of the largest root of hours and a very large sample uncertainty (Gospodinov, 2006). The estimator from the specification with HP filtered labour productivity growth performs similarly to the differenced estimator although it is slightly biased and more dispersed.…”
Section: Monte Carlo Experimentsmentioning
confidence: 81%
“…While the levels VAR appears to provide a more reliable framework for analysis in this setup, it may also produce biased and highly variable IRF estimates especially if hours worked are a near-integrated process. Imposing additional restrictions on the model (see, for example, Gospodinov, 2006) can lead to improved inference for the structural parameters and impulse responses.…”
Section: Resultsmentioning
confidence: 99%
See 3 more Smart Citations