Time-Series Modelling of Daily Tax Revenues
This paper discusses a time-series model for daily tax revenues. The model is an unobserved-components model with trend and seasonal components that vary over time. The seasonalities for inter-month and intra-month movements are modelled using stochastic cubic splines. The model is made operational and used to produce daily forecasts at the Dutch Ministry of Finance. A front-end for model configuration and data input is implemented with Visual C ++, while the econometrics and graphical diagnostics are build around Ox and SsfPack, the latter of which implements general procedures for the Kalman filter and state-space models.
|Date of creation:||01 Mar 1999|
|Contact details of provider:|| Postal: CEF99, Boston College, Department of Economics, Chestnut Hill MA 02467 USA|
Web page: http://fmwww.bc.edu/CEF99/
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- Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999.
"Statistical algorithms for models in state space using SsfPack 2.2,"
Royal Economic Society, vol. 2(1), pages 107-160.
- Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998. "Statistical Algorithms for Models in State Space Using SsfPack 2.2," Discussion Paper 1998-141, Tilburg University, Center for Economic Research.
- Harvey, Andrew & Koopman, Siem Jan & Riani, Marco, 1997. "The Modeling and Seasonal Adjustment of Weekly Observations," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 354-368, July.
- Harvey, Andrew C & Koopman, Siem Jan, 1992. "Diagnostic Checking of Unobserved-Components Time Series Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 377-389, October.
- Ooms, M. & Franses, Ph.H.B.F., 1998. "A seasonal periodic long memory model for monthly river flows," Econometric Institute Research Papers EI 9842, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute. Full references (including those not matched with items on IDEAS)