In this paper the Box-Jenkins approach to the building of seasonal time series model is extended so that it is adequate to model seasonally integrated time series. To this end, the class of multiplicative ARIMA models is broadened in such a way that it allows to describe time series integrated at a few of the seasonal frequencies. Thus, tests for seasonal unit roots are not considered as a rival modeling approach, but can be used in the identification stage to decide the transformation inducing stationarity. The fit model is used to generate forecasts and to estimate unobservable components. The enhanced Box-Jenkins approach is illustrated modeling the Spanish Industrial Production Index.
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