Linking series generated at different frequencies This work is part of a PhD dissertation presented at the University of California, San Diego (1999)
AbstractThis 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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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.
Volume (Year): 27 (2008)
Issue (Month): 2 ()
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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966
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- Qian, Hang, 2013. "Vector Autoregression with Mixed Frequency Data," MPRA Paper 47856, University Library of Munich, Germany.
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