Time-Series Modelling of Daily Tax Revenues
AbstractThis 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.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 1999 with number 312.
Date of creation: 01 Mar 1999
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