Article in Journal

Months for cyclical dominance and the Ifo Business Climate

Klaus Abberger, Wolfgang Nierhaus
ifo Institut für Wirtschaftsforschung, München, 2009

ifo Schnelldienst, 2009, 62, Nr. 07, 11-19

Business-cycle indicators should signal the cyclical developments in economic activity reliably and in a timely fashion. Important indicators for the analysis of German economic activity are, for example, the Ifo Business Climate, Industrial production and incoming orders in manufacturing. However, in all economic activity indicators the business-cycle signal they contain is always accompanied by unsystematic noise or an "interfering signal". For this reason an important quality criterion for economic activity indicators is the relationship contained in the time series between business cycle signal and interfering signal. This article presents two important measurement criteria - the IC relation (ratio of the average amplitudes of the irregular to the cyclical factor) and MCD measure (months for cyclical dominance) that builds on this; with these seasonally adjusted time series can be analysed with regard to the order of magnitude of irregular components to smooth business-cycle components. Then an examination is made of the quality of the Ifo Business Climate and its components in comparison with important indicators of the official statistics with regard to the two criteria mentioned above. The presented results show that both the business climate for manufacturing as well as the business climate for industry and trade perform very well in terms of the MCD criterion. The Ifo Business Climate is thus a monthly business cycle indicator which is very timely, gives early signals for business activity and in addition contains a very clear, i.e., cyclically significant, economic activity signal. For this reason the Ifo Business Climate is rightly regarded as a key indicator for the appraisals of the business trend in Germany.

JEL Classification: E320

Included in

Journal (Complete Issue)
ifo Institut für Wirtschaftsforschung, München, 2009