Economics at your fingertips  

Forecasting cointegrated nonstationary time series with time-varying variance

Yundong Tu and Yanping Yi

Journal of Econometrics, 2017, vol. 196, issue 1, 83-98

Abstract: In cointegrated vector autoregressive (VAR) models, error correction terms often have indeterminate effects on forecasting, thus we are concerned with inclusion or exclusion of the cointegration relation in forecast. This paper considers the model averaging strategies for cointegrated VAR models with heterogeneous variance or variance breaks. The estimated cointegration rank along with other data information are used to formulate the model averaging weights. This specific but unknown pattern of time-varying variances has nontrivial effects on the choices of model weights. Our numerical results strongly advocate the Mallows averaging estimator, but caution against the commonly used pre-testing approach.

Keywords: Cointegration; Error correction model; Model averaging; Pre-testing; Time-varying variance (search for similar items in EconPapers)
JEL-codes: C32 C52 C53 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

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:

DOI: 10.1016/j.jeconom.2016.09.012

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Haili He ().

Page updated 2020-05-02
Handle: RePEc:eee:econom:v:196:y:2017:i:1:p:83-98