Seite - 102 - in The Austrian Business Cycle in the European Context

102 the dynamic factor approach revealed some important informa- tion about sector-specific cyclical behaviour. In order to give some impression of the difference between just fil- tered series and those filtered by the same technique, but further processed by the dynamic factor model, Figure 9 plots both series for autGVAex, with the thin line representing just filtered values and the bold one the common component represented in this time series. As can be observed the series just filtered for certain frequencies exhibits larger amplitudes and is not as smooth as the one repre- sented by the common variance. Figure 1 O shows the same series, but for HP-filtered data. Again, the thin line marks the just filtered series and the bold one the common component. Again, the common component behaves more smoothly, but there seems to be no difference in amplitudes. In both cases it becomes apparent that there are dissimilarities be- tween the just filtered series and the one representing only its common component content. Differences show up not only in the number of peaks and troughs (and therefore of cycles), but also with regard to the dates of turning points, implying differences in leads and lags. However, while in general the leads and lags according to the cross-correlation criterion deviate only modestly from the just fil- tered data set, the leading and lagging behaviour is different for the series gerGHI and ger JK, which indicates that their idiosyn- cratic cycles play an important role in their data generation proc- ess. Again, this can be visualised by plotting them, as given in Fig- ures 11 and 12.