Linking series generated at different frequencies

Linking series generated at different frequencies

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Article ID: iaor20091461
Country: United Kingdom
Volume: 27
Issue: 2
Start Page Number: 95
End Page Number: 108
Publication Date: Mar 2008
Journal: International Journal of Forecasting
Authors: ,
Keywords: ARIMA processes, Kalman filter
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.

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