Seite - 21 - in The Austrian Business Cycle in the European Context

21 tional working day due to specific calendar constellations will not yield the same value added as in a boom. As a consequence, the business cycle reaction of calendar effects shows up wrongly in the business cycle itself, if calendar effects are estimated as being orthogonal. But this should bias only the amplitude of the business cycle, but not interfere with the dating of the cycle. 3.2.3 Seasonal variations These high frequency movements can interfere with the dating of the overall peaks and troughs. Sims (1993) and Hansen - Sargent ( 1993) have shown that seasonal pre-filtering is essential in business cycle analysis in order to avoid a distortion of the business cycle pattern. Therefore, the largest part of studies is based on the analysis of seasonally adjusted time series, but there are also good arguments for considering unadjusted series as well. Cubadda ( 1999) found that in the case of existence of seasonal co-integration between analysed time series, the results for unadjusted and adjusted time series can be different. Despite the theoretically difficult economic implication of having a steady state trend showing seasonal varia- tions, he argues in favour of using unadjusted time series and clearing them for seasonal variations within the same framework used for business cycle analysis. In a similar direction points the study by Joger - Kunst ( 1990) who showed that the process of sea- sonal adjustment spuriously amplifies the persistence of variables. There are several approaches of clearing for seasonal variations which estimate the trend and the cycle within one framework, as proposed by Cubadda ( 1999)35• In unobserved components 35 It has to be noted, that the application of band-pass filters for frequencies of the business cycle not only cancels out the trend component but also seasonal varia- tions. It is unclear whether this is conforming to a separation process within one framework in the sense of Cubadda (1999).