A comparison of sequential and information-based methods for determining the co-integration rank in heteroskedastic VAR models

Cavaliere, Giuseppe ; De Angelis, Luca ; Rahbek, Anders ; Taylor, A.M.Robert (2013) A comparison of sequential and information-based methods for determining the co-integration rank in heteroskedastic VAR models. Bologna, IT: Dipartimento di Scienze Statistiche "Paolo Fortunati", Alma Mater Studiorum Università di Bologna, p. 20. DOI 10.6092/unibo/amsacta/3731. In: Quaderni di Dipartimento. Serie Ricerche ISSN 1973-9346.
Full text available as:
[img]
Preview
PDF
License: Creative Commons Attribution Non-commercial No Derivatives

Download (550kB) | Preview

Abstract

In this paper we investigate the behaviour of a number of methods for estimating the co-integration rank in VAR systems characterized by heteroskedastic innovation processes. In particular we compare the efficacy of the most widely used information criteria, such as AIC and BIC, with the commonly used sequential approach of Johansen (1996) based around the use of either asymptotic or wild bootstrap-based likelihood ratio type tests. Complementing recent work done for the latter in Cavaliere, Rahbek and Taylor (2013, Econometric Reviews, forthcoming), we establish the asymptotic properties of the procedures based on information criteria in the presence of heteroskedasticity (conditional or unconditional) of a quite general and unknown form. The relative finite-sample properties of the different methods are investigated by means of a Monte Carlo simulation study. For the simulation DGPs considered in the analysis, we find that the BIC-based procedure and the bootstrap sequential test procedure deliver the best overall performance in terms of their frequency of selecting the correct co-integration rank across different values of the co-integration rank, sample size, stationary dynamics and models of heteroskedasticity. Of these the wild bootstrap procedure is perhaps the more reliable overall since it avoids a significant tendency seen in the BIC-based method to over-estimate the co-integration rank in relatively small sample sizes.

Abstract
Document type
Monograph (Working Paper)
Creators
CreatorsAffiliationORCID
Cavaliere, Giuseppe
De Angelis, Luca
Rahbek, Anders
Taylor, A.M.Robert
Keywords
Cointegrazione, Wild bootstrap, Statistic traccia, Criteri di informazione, Determinazione rango, Eteroschedasticità Co-integration; Wild bootstrap; Trace statistic; Information criteria; Rank determi- nation; Heteroskedasticity.
Subjects
ISSN
1973-9346
DOI
Deposit date
31 Jul 2013 14:05
Last modified
06 Aug 2013 09:23
URI

Other metadata

Downloads

Downloads

Staff only: View the document

^