Page - 123 - in The Austrian Business Cycle in the European Context

123 leads and lags of each series with respect to the reference series are of rather limited reliability. Compared with results of other ap- proaches of filtering time series, they are not similar to any of them, whereas there is some similarity between HP- and BK-filtered data. Despite the fact that this erratic series shows a plethora of ups and downs, the criteria set in the Bry-Boschan procedure for identifying ups and downs as turning points are only rarely fulfilled such that surprisingly few turning points are detected. Nevertheless, such dating seems to be arbitrary, as a transformation by a dynamic factor model yields a completely different dating calendar. The unsystematic changes reflected by the statistics concerning the length of cycles and phases provide evidence that this dating is unreliable. Under these conditions, the extraction of a common component by a dynamic factor model approach is difficult, leading to only small explanatory power of the common compo- nent (represented by two dynamic factors) for all series. For HP-filtered series, results are more promising. Cross-correlations for just filtered series are only marginally smaller than for BK-filtered series and give for all series the same picture of leads and lags according to the highest correlation criterion. For mean deviations calculated by (Bartlett window smoothed) cross-spectra, the pic- ture differs somewhat, but not very much. For dynamic-factor- model-transformed series, the results are again quite similar con- cerning the cross-correlations for the respective series with the ref- erence series. Only for autJK (the Austrian financial intermediation, real estate and business service sector), the cross-correlation of the common component suggests a lead of 4 quarters, whereas it shows a coincident behaviour for just filtered series. After the application of the Bry-Boschan dating procedure, the similarities between HP- and BK-filtered data vanish. There again, the high-frequency component outside the business cycle fre- quency band included in HP-filtered series makes the detection of turning points a difficult and ambiguous task. Like in the case of first-order differences, only few spikes are able to pass the criteria for turning points. Therefore, the turning points given for the HP-