This paper proposes a novel wavelet-based approach for constructing composite indicators. The wavelet-based methodology exploits the ability of wavelet analysis to analyze the relationships between variables on a scale-by-scale, rather than aggregate, basis. A wavelet-based index which combines several "scale-based" sub-indexes is constructed by using a "scale-by-scale" selection of the components included in the OECD composite leading indicator (CLI) for the US. The comparison with the CLI and its derived measures indicate that the wavelet-based composite index tends to provide early signals of business cycle turning points well in advance of the OEDC CLI. Moreover we find that the reliability of the signals tends to increase considerably when the sub-index obtained from the time scale components corresponding to minor cycles, i.e. 2-4 years, is removed from the overall wavelet-based index.
Making leading indicators more leading. A "wavelet-based" method for the construction of composite leading indexes / Gallegati, Marco. - In: OECD JOURNAL: JOURNAL OF BUSINESS CYCLE MEASUREMENT AND ANALYSIS. - ISSN 1995-2880. - STAMPA. - 2014:1(2014), pp. 67-87. [10.1787/jbcma-2014-5jxx56gqmhf1]
Making leading indicators more leading. A "wavelet-based" method for the construction of composite leading indexes
GALLEGATI, Marco
2014-01-01
Abstract
This paper proposes a novel wavelet-based approach for constructing composite indicators. The wavelet-based methodology exploits the ability of wavelet analysis to analyze the relationships between variables on a scale-by-scale, rather than aggregate, basis. A wavelet-based index which combines several "scale-based" sub-indexes is constructed by using a "scale-by-scale" selection of the components included in the OECD composite leading indicator (CLI) for the US. The comparison with the CLI and its derived measures indicate that the wavelet-based composite index tends to provide early signals of business cycle turning points well in advance of the OEDC CLI. Moreover we find that the reliability of the signals tends to increase considerably when the sub-index obtained from the time scale components corresponding to minor cycles, i.e. 2-4 years, is removed from the overall wavelet-based index.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.