Norges Bank paper tries to extract high-frequency forecasts from low-frequency data
Researchers find low-frequency information can be important
Low-frequency information is important in forecasting high-frequency variables, according to research published on October 29 by Norges Bank.
Forecasting low-frequency data such as quarterly GDP figures using high-frequency variables such as monthly data is common, but in the working paper Using low frequency information for predicting high frequency variables, authors Claudia Foroni, Pierre Guérin and Massimiliano Marcellino flip the model around.
They use a new model to capture the "dynamic
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