4.6 Article

Weekly economic activity: Measurement and informational content

期刊

INTERNATIONAL JOURNAL OF FORECASTING
卷 39, 期 1, 页码 228-243

出版社

ELSEVIER
DOI: 10.1016/j.ijforecast.2021.10.010

关键词

Business cycle index; Dynamic factor model; High-frequency data; Nowcasting; Seasonal adjustment; Forecast evaluation; Covid-19

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We have constructed a composite index to measure the real activity of the Swiss economy on a weekly basis, using a novel high-frequency data set. Our six-step procedure for extracting precise business cycle signals from the raw data highlights the importance of our proposed adjustment procedure, as our weekly index outperforms comparable indices and established monthly indicators in forecasting GDP growth. These findings can contribute to the improvement of other high-frequency indicators.
We construct a composite index to measure the real activity of the Swiss economy on a weekly frequency. The index is based on a novel high-frequency data set capturing economic activity across distinct dimensions over a long time horizon. We propose a six -step procedure for extracting precise business cycle signals from the raw data. By means of a real-time evaluation, we highlight the importance of our proposed adjustment procedure: (i) our weekly index significantly outperforms a comparable index without adjusted input variables; and (ii) the weekly index outperforms established monthly indicators in nowcasting GDP growth. These insights should help improve other recently developed high-frequency indicators.(c) 2021 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

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