Högskolan i Skövde

his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Optimal lag-length choice in stable and unstable VAR models under situations of homoscedasticity and ARCH
Jönköping Int Business Sch, Dept Econ, Jönköping, Sweden.
University of Skövde, School of Technology and Society.
2008 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 35, no 6, p. 601-615Article in journal (Refereed) Published
Abstract [en]

The performance of different information criteria - namely Akaike, corrected Akaike (AICC), Schwarz-Bayesian (SBC), and Hannan-Quinn - is investigated so as to choose the optimal lag length in stable and unstable vector autoregressive (VAR) models both when autoregressive conditional heteroscedasticity (ARCH) is present and when it is not. The investigation covers both large and small sample sizes. The Monte Carlo simulation results show that SBC has relatively better performance in lag-choice accuracy in many situations. It is also generally the least sensitive to ARCH regardless of stability or instability of the VAR model, especially in large sample sizes. These appealing properties of SBC make it the optimal criterion for choosing lag length in many situations, especially in the case of financial data, which are usually characterized by occasional periods of high volatility. SBC also has the best forecasting abilities in the majority of situations in which we vary sample size, stability, variance structure (ARCH or not), and forecast horizon (one period or five). frequently, AICC also has good lag-choosing and forecasting properties. However, when ARCH is present, the five-period forecast performance of all criteria in all situations worsens.

Place, publisher, year, edition, pages
Routledge, 2008. Vol. 35, no 6, p. 601-615
Keywords [en]
VAR, lag length, information criteria, Monte Carlo simulations, ARCH, stability
National Category
Economics
Research subject
Humanities and Social sciences
Identifiers
URN: urn:nbn:se:his:diva-2944DOI: 10.1080/02664760801920473ISI: 000256403300001Scopus ID: 2-s2.0-46249118587OAI: oai:DiVA.org:his-2944DiVA, id: diva2:210693
Available from: 2009-04-03 Created: 2009-04-03 Last updated: 2017-12-13Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Hatemi-J., Abdulnasser

Search in DiVA

By author/editor
Hatemi-J., Abdulnasser
By organisation
School of Technology and Society
In the same journal
Journal of Applied Statistics
Economics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 377 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf