This work is part of a PhD dissertation presented at the University of California, San Diego (1999).

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Linking series generated at different frequencies

This work is part of a PhD dissertation presented at the University of California, San Diego (1999).

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Author Info
Namwon Hyung (Department of Economics, University of Seoul, Seoul, Korea)
Clive W.J. Granger (Department of Economics, University of California, San Diego, California, USA)

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Abstract

This is a report on our studies of the systematical use of mixed-frequency datasets. We suggest that the use of high-frequency data in forecasting economic aggregates can increase the accuracy of forecasts. The best way of using this information is to build a single model that relates the data of all frequencies, for example, an ARMA model with missing observations. As an application of linking series generated at different frequencies, we show that the use of a monthly industrial production index improves the predictability of the quarterly GNP. Copyright © 2008 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1042
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 27 (2008)
Issue (Month): 2 ()
Pages: 95-108
Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Handle: RePEc:jof:jforec:v:27:y:2008:i:2:p:95-108

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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