Smooth and timely business cycle indicators for noisy Swedish data

Smooth and timely business cycle indicators for noisy Swedish data

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Article ID: iaor1997812
Country: Netherlands
Volume: 12
Issue: 4
Start Page Number: 389
End Page Number: 402
Publication Date: Oct 1996
Journal: International Journal of Forecasting
Authors: ,
Keywords: business cycles
Abstract:

Noise in statistical time series is often overlooked when selecting the best forecasting model by minimizing forecast errors. An ‘error’ implies that one knows the true (noise-free) outcome. Instead of merely trying to forecast a noisy outcome, the authors construct entirely new indicators, based on business tendency survey data and statistical time series. False turning point signals are avoided by exponential smoothing. A special trigger is found in the joint behavior of model generated smoothed and unsmoothed forecasts, by which smoothing can be switched off in sharp turns, and this avoids late turning point signals that would occur with smoothed data.

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