Page - 150 - in The Austrian Business Cycle in the European Context

150 data set can also lead to different dates. This has not necessarily to do with revisions of GDP itself, but with the seasonal adjustment procedure. As this is usually done by an unobserved components model or some other filtering procedure (like X12-ARIMA), past values could be slightly revised with every new observation forth- coming. Such marginal revisions can easily change turning point locations, like for two of the troughs in Table 4, if growth rates are close to zero. Table 4: Business cycle turning points for Austria, Germany and the euro area Eurl 2 GDP growth In Percent Quarters 2Q1977 ---0.01 3Q1977 ---0.05 2Q1980 ---0.60 3Q1980 ---0. 19 4Q1980 ---0.02 2Q1982 ---0.01 3Q1982 ---0.66 4Q1982 ---0.02 2Q1992 ---0.87 3Q1992 ---0.40 4Q1992 ---0.26 1Q1993 ---0.39 2Q1993 ---0.05 Source: Own calculations. Apart from this shift in turning points, the use of the rule of two negative growth rates (first-order differences of logged data like in our study) for dating troughs seems to be superior to using them in combination with the Bry-Boschan routine like in our study. Never- theless, this rule concentrates more on the classical cycle showing much fewer troughs than concepts drawing explicitly on deviation cycles.