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Related-variables selection in temporal disaggregation

Listed author(s):
  • Kosei Fukuda

    (College of Economics, Nihon University, Tokyo, Japan)

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.

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File URL: http://hdl.handle.net/10.1002/for.1115
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 28 (2009)
Issue (Month): 4 ()
Pages: 343-357

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Handle: RePEc:jof:jforec:v:28:y:2009:i:4:p:343-357
DOI: 10.1002/for.1115
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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