Modelovanie sezónnosti úspor domácností stavovými modelmi
SEASONALITY MODELLING OF TIME AND SAVINGS DEPOSITS OF HOUSEHOLDS BY STATE- SPACE MODELS

Summary/Abstract: Lots of econometric models discussed in the literature are the models that contain trend and error components only. We now present the method seldom used for modelling trend (deterministic component), seasonal and error component using the dynamic models in state-space form. Model parameters are time varying Their development is estimeted adaptively by the Kalman recursions. In recent years quantitative systems based on the state-space representation have been used. Based on the fact that economic and financial time series of quarterly and monthly or high frequency data contain seasonality, we do not take the seasonality into account, because the econometric model and forecasting method become only second best. A widely used method to incorporate the seasonality into the econometric models is the approach known as the decomposition method. Unfortunately, the decomposition method has some disadvantage. The decomposi-tion method is basically intuitive and there are a number of theoretical weaknesses in this approach and in estimating model parameters. State-space representation and the associated Kalman recursions have had a profound impact on time series modelling and many related areas. In this paper we investigate the application of state-space models and the Kalman recursions to quarterly time and savings deposits of households forecasting and stress of the problems encountered with this modelling technique. The time and savings deposits of households is a model with a quarterly time step. Original data are quarterly time series providing a total of 24 observations.

• Details
• Contents