Arbeitspapier
Time Series Modelling of Daily Tax Revenues
We provide a detailed discussion of the time series modelling of daily tax revenues. The mainfeature of daily tax revenue series is the pattern within calendar months. Standard seasonal timeseries techniques cannot be used since the number of banking days per calendar month varies andbecause there are two levels of seasonality: between months and within months.We start the analysis with a periodic regression model with time varying parameters.This modelis then extended with a component for intra-month seasonality, which is specified as a stochasticcubic spline. State space techniques are used for recursive estimation and evaluation as they allowfor irregular spacing of the time series.The model is recently made operational and used for daily forecasting at the Dutch Ministry ofFinance. For this purpose a front-end for model configuration and data input is implemented withVisual C++, while statistical tools and graphical diagnostics are built around Ox and SsfPack. Wepresent the current model and forecasting results up to December 1999. The model and itsforecasts are evaluated.
- Language
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Englisch
- Bibliographic citation
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Series: Tinbergen Institute Discussion Paper ; No. 01-032/4
- Classification
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Wirtschaft
- Subject
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Steuereinnahmen
Zeitreihenanalyse
Schätztheorie
Theorie
Niederlande
- Event
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Geistige Schöpfung
- (who)
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Koopman, Siem Jan
Ooms, Marius
- Event
-
Veröffentlichung
- (who)
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Tinbergen Institute
- (where)
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Amsterdam and Rotterdam
- (when)
-
2001
- Handle
- Last update
-
10.03.2025, 11:43 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Koopman, Siem Jan
- Ooms, Marius
- Tinbergen Institute
Time of origin
- 2001
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