Impulse Response Analysis in Vector Autoregressions with Unknown Lag Order

Lutz Kilian

Journal of Forecasting, 2001, vol. 20, issue 3, 161-79

Abstract: We show that the effects of overfitting and underfitting a vector autoregressive (VAR) model are strongly asymmetric for VAR summary statistics involving higher-order dynamics (such as impulse response functions, variance decompositions, or long-run forecasts). Underfit models often underestimate the true dynamics of the population process and may result in spuriously tight confidence intervals. These insights are important for applied work, regardless of how the lag order is determined. In addition, they provide a new perspective on the trade-offs between alternative lag order selection criteria. We provide evidence that, contrary to conventional wisdom, for many statistics of interest to VAR users the point and interval estimates based on the AIC compare favourably to those based on the more parsimonious Schwarz Information Criterion and Hannan-Quinn Criterion. Copyright © 2001 by John Wiley & Sons, Ltd.

Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (108)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
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:jof:jforec:v:20:y:2001:i:3:p:161-79

Access Statistics for this article

Journal of Forecasting is currently edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().