Related-variables selection in temporal disaggregation

Kosei Fukuda ()

Journal of Forecasting, 2009, vol. 28, issue 4, 343-357

Abstract: Two related-variables selection methods for temporal disaggregation are proposed. In the first method, the hypothesis tests for a common feature (cointegration or serial correlation) are first performed. If there is a common feature between observed aggregated series and related variables, the conventional Chow-Lin procedure is applied. In the second method, alternative Chow-Lin disaggregating models with and without related variables are first estimated and the corresponding values of the Bayesian information criterion (BIC) are stored. It is determined on the basis of the selected model whether related variables should be included in the Chow-Lin model. The efficacy of these methods is examined via simulations and empirical applications. Copyright © 2008 John Wiley & Sons, Ltd.

Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1002/for.1115 Link to full text; subscription required (text/html)

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: https://EconPapers.repec.org/RePEc:jof:jforec:v:28:y:2009:i:4:p:343-357

DOI: 10.1002/for.1115

Access Statistics for this article

Journal of Forecasting is currently edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().