Page - 119 - in The Austrian Business Cycle in the European Context

119 stantial difference between looking at average and median leads and lags, respectively. This is pointing to an unstable pattern of leads and lags, where averages are driven by extreme values. In this respect, working with data transformed by a dynamic factor model did not lead to a clearer picture. Again, the use of HP-filtered data shows a more consistent picture for average and median leads and lags, which can probably be attributed to the lower content of high-frequency variation. But again, some ambiguous results emerged. When the results pre- sented in Table A 9 b are compared with the leads and lags de- tected according to the cross-correlation criteria of Table A 7 b, it becomes apparent that medians are more similar to those. Only for autJK, the Austrian sector of financial intermediation, real es- tate and business services and eurGDPex, the euro area GDP (ex- cluding Austria and Germany), turning point averages and medi- ans are pointing to a leading behaviour, which is not confirmed if one looks only at the cross-correlations of their respective com- mon components. In the case of BK-filtered data, the results for averages and medi- ans shown in Table A 9 c seem to be quite similar to the leading and lagging properties according to cross-correlations in Ta- ble A 7 c. The moments of all series are not far away from being coincident, as reflected by cross-correlations. Only for eurGDPex - the euro area GDP without Austria and Germany-, an average lead of more than one quarter is calculated, but this result is not supported by its median shift that favours a coincident behaviour. If we clear the BK-filtered data for idiosyncratic cycles, resulting turning points seem to behave quite stable as the rounded aver- age leads and lags coincide in all but the above-mentioned case with its medians. This was not as much the case for just filtered se- ries, as can be seen in Table A 3 c. According to the results of the turning point analysis for common components with respect to the reference series based on BK- filtered data, the Austrian construction industry (autF) shows on