Is TRAMO-SEATS automatic identification of Reg-ARIMA ... - Cemfi

ABSTRACTIn so far that –as Hawking and Mlodinow state– “there can be no modelindependenttest of reality,” time series analysis applied to large sets of series(perhaps several thousands) needs an automatic model identification (AMI)procedure. The presentation will discuss the results of the automaticidentification of models of the regression-ARIMA (reg-ARIMA) type in programsTRAMO-SEATS. The procedure identifies several types of outliers and calendareffects through regression, and identifies the ARIMA model for the stochasticseries. Interpolators of missing values (if any) and forecasts of the series areobtained, as well as MMSE estimators and forecasts of the unobservedcomponents contained in the series (in particular, of the seasonally adjustedseries). Two sets of series are treated: one with 50000 simulated series,generated by 50 different ARIMA models; the second with 13691 real economicseries of different lengths. The first set shows the accuracy of the procedure inidentifying the correct model; the second set shows the ability of the procedureto provide a satisfactory model for actual series, as evidenced by the validity ofthe n.i.i.d. assumption for the residuals and by the performance of the out-ofsampleforecasts. A comparison with the AMI procedure in the present X12-ARIMA and DEMETRA+ programs (based on older versions of the TRAMO´s AMI)is made.For monthly series with lengths not exceeding 30 years the TRAMO + AMIprocedure is found remarkably reliable. (For very long series kurtosis of theresiduals becomes the biggest problem.) Still, the procedure certainly providesan excellent benchmark and a good starting point when a careful manualidentification is intended.1