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This paper compares seasonal ARIMA models as presented in Box and Jenkins I models with ARIMA component (structural) models as presented in Harvey (1989). Both are augmented as appropriate with the same regression variables to account for calendar effects, level shifts, and additive outliers. The models are compared on a set of 40 Census Bureau monthly time series in regard to fit using AIC and related statistics. Bell and Pugh (1990) made similar comparisons of ARIMA models with the basic structural model BSM). This paper extends their work by also considering ARIMA component k models with trigonometric seasonal components. For the 40 time series considered, AIC and the other model comparison statistics express a strong overall preference for the ARIMA models over the ARIMA component models.
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