Optimal lag-length choice in stable and unstable VAR models under situations of homoscedasticity and ARCH

Hacker, R. Scott and Hatemi-J, Abdulnasser 2008, Optimal lag-length choice in stable and unstable VAR models under situations of homoscedasticity and ARCH, Journal of applied statistics, vol. 35, no. 6, pp. 601-615.

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Title Optimal lag-length choice in stable and unstable VAR models under situations of homoscedasticity and ARCH
Author(s) Hacker, R. Scott
Hatemi-J, Abdulnasser
Journal name Journal of applied statistics
Volume number 35
Issue number 6
Start page 601
End page 615
Publisher Routledge
Place of publication London, England
Publication date 2008-06
ISSN 0266-4763
1360-0532
Keyword(s) VAR
lag length
information criteria
Monte Carlo simulations
ARCH
stability
Summary 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.
Language eng
Field of Research 140305 Time-Series Analysis
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2008, Taylor & Francis
Persistent URL http://hdl.handle.net/10536/DRO/DU:30017224

Document type: Journal Article
Collection: School of Accounting, Economics and Finance
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