Page - 86 - in The Austrian Business Cycle in the European Context

86 erence business cycle according to the ad-hoc method. The cy- clical components of all other series are analysed in relation to that reference series in order to uncover their leading or lagging properties. Despite the fact that GV A less agriculture and forestry seems to be a sensible weighted and measured indicator of aggregate eco- nomic activity, it does not mean that the driving force behind business cycle fluctuations can best be extracted by analysing that series. A different indicator that weighs together various eco- nomic time series of different origin could be more capable of rep- resenting the cyclical variations contained in different economic time series. Therefore, a second approach to determine the busi- ness cycle has been followed by constructing a composite eco- nomic indicator. As already mentioned in chapter 4, the construction of composite economic indices according to the empirical NBER approach does not seem to be feasible here. As this is basically a rather arbi- trary method, an acceptable outcome depends on the contribu- tions by many experts. Instead, a more formal approach is fol- lowed in the present study by setting up a dynamic factor model in order to isolate the common driving force of all filtered series. Thus, two different methods have been chosen to identify the cy- cle: one ad-hoc method, which determines the business cycle by the cyclical frequencies found in the gross value added excluding agriculture and forestry, and one multivariate approach, based on a composite index which has been constructed by setting up a dynamic factor model. 8.2. 1. Ad-hoc selection of the business cycle reference series In order to get a first idea of the dynamics of the Austrian business cycle, represented by the filtered series of gross value added ex- cluding agriculture and forestry (autGVAex), and a possible co- movement with euro area GDP, the following graphs show BK-