Bootstrap inference for impulse response functions in factor‐augmented vector autoregressions

Yohei Yamamoto

Journal of Applied Econometrics, 2019, vol. 34, issue 2, 247-267

Abstract: In this study, we consider residual‐based bootstrap methods to construct the confidence interval for structural impulse response functions in factor‐augmented vector autoregressions. In particular, we compare the bootstrap with factor estimation (Procedure A) with the bootstrap without factor estimation (Procedure B). Both procedures are asymptotically valid under the condition T/N→0, where N and T are the cross‐sectional dimension and the time dimension, respectively. However, Procedure A is also valid even when T/N→c with 0 ≤ c

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
https://doi.org/10.1002/jae.2659

Related works:
Working Paper: Bootstrap Inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions (2016)
Working Paper: Bootstrap Inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:japmet:v:34:y:2019:i:2:p:247-267

Ordering information: This journal article can be ordered from
http://www3.intersci ... e.jsp?issn=0883-7252

Access Statistics for this article

Journal of Applied Econometrics is currently edited by M. Hashem Pesaran

More articles in Journal of Applied Econometrics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().