Abstract
The problem of choosing between the direct and the indirect method for the seasonal adjustment of aggregate time series is addressed. Different multivariate approaches are proposed in order to define properly optimised aggregation weights for the component time series. The new weighing systems help in discriminating between the classical methods and may perform better than the weights assigned a-priori. Applications on real economic series are shown.
Acknowledgments: This research was supported by an ESPRIT (29.741 TESS) grant. We are very much indebted to Prof. Carlo Lauro for providing us with the main ideas behind this paper as well as for strongly supporting and encouraging the further developments.
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© 2000 Springer-Verlag Berlin Heidelberg
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Davino, C., Esposito, V. (2000). Multivariate approaches for aggregate time series1 . In: Bethlehem, J.G., van der Heijden, P.G.M. (eds) COMPSTAT. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57678-2_31
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DOI: https://doi.org/10.1007/978-3-642-57678-2_31
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1326-5
Online ISBN: 978-3-642-57678-2
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