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Seasonal and Cyclical Properties of Ifo Business Test Variables / Saisonale und zyklische Eigenschaften von ifo Konjunkturtest Variablen

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  • Flaig Gebhard

    (ifo Institut für Wirtschaftsforschung, Poschingerstr. 5, D-81679 München. Tel.: ++49/+89/92 24 13 79)

Abstract

In this paper, an Unobserved Components Model is used to decompose the balances of Ifo Business survey data into the cyclical, the seasonal and the irregular components, as well as the working day effect. The empirical results show that the total cycle consists of three subcycles with about 3, 5 and 11 years. Each subcycle of the assessment variable is “similar” to the corresponding subcycle of the expectations variable. The seasonal pattern is changing over time and the working day effect is significant for the assessment of the current business situation and for the Ifo Business Climate, but not for the expectation series.

Suggested Citation

  • Flaig Gebhard, 2003. "Seasonal and Cyclical Properties of Ifo Business Test Variables / Saisonale und zyklische Eigenschaften von ifo Konjunkturtest Variablen," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 223(5), pages 556-570, October.
    • Handle: RePEc:jns:jbstat:v:223:y:2003:i:5:p:556-570
    DOI: 10.1515/jbnst-2003-0504
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    References listed on IDEAS

    as
    1. Gebhard Flaig, 2001. "Trend and Cycles in U.S. Real GDP," CESifo Working Paper Series 607, CESifo.
    2. Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
    3. Gebhard Flaig, 2002. "Unoberserved Components Models for Quarterly German GDP," CESifo Working Paper Series 681, CESifo.
    4. Agustín Maravall, 1996. "Unobserved Components in Economic Time Series," Working Papers 9609, Banco de España.
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    Cited by:

    1. Klaus Abberger & Sascha Becker & Barbara Hofmann & Klaus Wohlrabe, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung – Bestand, Verwendung und Zugang," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 1(1), pages 27-42, June.
    2. Stefan Mittnik & Peter Zadrozny, 2005. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly Ifo Business Conditions Data," Contributions to Economics, in: Jan-Egbert Sturm & Timo Wollmershäuser (ed.), Ifo Survey Data in Business Cycle and Monetary Policy Analysis, pages 19-48, Springer.
    3. Steffen Henzel, 2015. "Forecasting Accuracy of the Ifo Business Survey – Influence of New Seasonal Adjustment with X-13ARIMA-SEATS," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(01), pages 59-63, January.
    4. Sascha O. Becker & Klaus Wohlrabe, 2008. "European Data Watch: Micro Data at the Ifo Institute for Economic Research – The “Ifo Business Survey”, Usage and Access," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 128(2), pages 307-319.

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