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Markov-Switching and the Ifo Business Climate: the Ifo Business Cycle Traffic Lights

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  • Klaus Abberger

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  • Wolfgang Nierhaus

Abstract

Business cycle indicators are used to assess the economic situation of countries or regions. They are closely watched by the public, but are not easy to interpret. Does a current movement of the indicator signal a turning point or not? With the help of Markov Switching Models movements of indicators can be transformed in probability statements. In this article, the most important leading indicator of the German business cycle, the Ifo Business Climate, is described by a Markov Switching Model. Real-time probabilities for the current business-cycle regime are derived and presented in an innovative way: as the Ifo traffi c lights. JEL Classifi cation: E32, C22 Keywords: Ifo business climate, growth cycle, turning points, Markov-switching

Suggested Citation

  • Klaus Abberger & Wolfgang Nierhaus, 2010. "Markov-Switching and the Ifo Business Climate: the Ifo Business Cycle Traffic Lights," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(2), pages 1-13.
  • Handle: RePEc:oec:stdkab:5km4gzqtx248
    DOI: 10.1787/jbcma-2010-5km4gzqtx248
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    References listed on IDEAS

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    1. Klaus Abberger & Wolfgang Nierhaus, 2009. "Months for Cyclical Dominance und ifo Geschäftsklima," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(07), pages 11-19, April.
    2. Klaus Abberger & Klaus Wohlrabe, 2006. "Einige Prognoseeigenschaften des ifo Geschäftsklimas - Ein Überblick über die neuere wissenschaftliche Literatur," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(22), pages 19-26, November.
    3. Diebold, Francis X & Rudebusch, Glenn D, 1989. "Scoring the Leading Indicators," The Journal of Business, University of Chicago Press, vol. 62(3), pages 369-391, July.
    4. Daniel R. Smith & Allan Layton, 2007. "Comparing Probability Forecasts in Markov Regime Switching Business Cycle Models," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2007(1), pages 79-98.
    5. Goldfeld, Stephen M. & Quandt, Richard E., 1973. "A Markov model for switching regressions," Journal of Econometrics, Elsevier, vol. 1(1), pages 3-15, March.
    6. Potter, Simon M, 1999. "Nonlinear Time Series Modelling: An Introduction," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 505-528, December.
    7. Klaus Abberger & Wolfgang Nierhaus, 2007. "Das ifo Geschäftsklima und Wendepunkte der deutschen Konjunktur," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 60(03), pages 26-31, February.
    8. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, March.
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    10. repec:ces:ifosdt:v::y:2009:i::p:11-19 is not listed on IDEAS
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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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