Abstract
This article illustrates the seasonal adjustment procedure for bank deposits and loans in Italy focusing on the revision policy of seasonally adjusted data. Seasonal adjustment is conducted in a semi-automatic way, employing TRAMO–SEATS, one of the software packages most often used for the production of seasonally adjusted series. Regarding the frequency of data revisions, three alternative methods (current adjustment, concurrent adjustment and partial concurrent adjustment) are tested according to a quantitative criterion. An empirical application allows us to measure the speed of convergence of the estimates obtained with the aforementioned updating methods towards a ‘final’ value that can be considered a benchmark. The results suggest using the method of partial concurrent adjustment, which is based on the identification of the ARIMA model and of the deterministic components once a year, whereas the updating of the corresponding coefficients is undertaken every month.
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