Cavaliere, Giuseppe ;
Rahbek, Anders ;
Taylor, A.M. Robert
(2011)
Bootstrap determination of the co-integration rank in VAR models.
Bologna, IT:
Dipartimento di Scienze Statistiche "Paolo Fortunati", Alma Mater Studiorum Università di Bologna,
p. 15.
DOI
10.6092/unibo/amsacta/3130.
In: Quaderni di Dipartimento. Serie Ricerche
ISSN 1973-9346.
Full text available as:
Abstract
This paper discusses a consistent bootstrap implementation of the likelihood ratio [LR] co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates of the underlying VAR model which obtain under the reduced rank null hypothesis. A full asymptotic theory is provided which shows that, unlike the bootstrap procedure in Swensen (2006) where a combination of unrestricted and restricted estimates from the VAR model is used, the resulting bootstrap data are I(1) and satisfy the null co-integration rank, regardless of the true rank. This ensures that the bootstrap LR test is asymptotically correctly sized and that the probability that the bootstrap sequential procedure selects a rank smaller than the true rank converges to zero. Monte Carlo evidence suggests that our bootstrap procedures work very well in practice.
Abstract
This paper discusses a consistent bootstrap implementation of the likelihood ratio [LR] co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates of the underlying VAR model which obtain under the reduced rank null hypothesis. A full asymptotic theory is provided which shows that, unlike the bootstrap procedure in Swensen (2006) where a combination of unrestricted and restricted estimates from the VAR model is used, the resulting bootstrap data are I(1) and satisfy the null co-integration rank, regardless of the true rank. This ensures that the bootstrap LR test is asymptotically correctly sized and that the probability that the bootstrap sequential procedure selects a rank smaller than the true rank converges to zero. Monte Carlo evidence suggests that our bootstrap procedures work very well in practice.
Document type
Monograph
(Working Paper)
Creators
Keywords
Bootstrap; Co-integration; Trace statistic; Rank determination
Bootstrap; Cointegrazione; Statistica “traccia”; determinazione del rango
Subjects
ISSN
1973-9346
DOI
Deposit date
14 Oct 2011 08:08
Last modified
08 Nov 2011 10:04
URI
Other metadata
Document type
Monograph
(Working Paper)
Creators
Keywords
Bootstrap; Co-integration; Trace statistic; Rank determination
Bootstrap; Cointegrazione; Statistica “traccia”; determinazione del rango
Subjects
ISSN
1973-9346
DOI
Deposit date
14 Oct 2011 08:08
Last modified
08 Nov 2011 10:04
URI
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