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Das neue KOF Konjunkturbarometer – Version 2014

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Abstract

This paper presents a new composite leading indicator for the Swiss business cycle corresponding to the growth cycle concept. It is the result of another complete overhaul of the KOF Economic Barometer that has been published by the KOF Swiss Economic Institute on a monthly basis since 1976. In line with its tradition, the calculation of the new KOF Economic Barometer comprises two main stages. The first consists of the variable selection procedure; and in the second stage these variables are subsequently transformed into one leading indicator. Whereas in the previous versions of the KOF Economic Barometer six to 25 variables survived the first stage, the new – less discretionary and more automated – version selects hundreds of variables into the second stage. The increased number of variables underlying the second stage allows a relatively stable and robust KOF Economic Barometer that hence no longer has to rely on filtering techniques to reduce the noise in the final indicator.

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  • Michael Graff & Klaus Abberger & Boriss Siliverstovs & Jan-Egbert Sturm, 2014. "Das neue KOF Konjunkturbarometer – Version 2014," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 8(1), pages 91-106, March.
    • Handle: RePEc:kof:anskof:v:8:y:2014:i:1:p:91-106
    DOI: 10.3929/ethz-a-005427569
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    1. Filippo Altissimo & Antonio Bassanetti & Riccardo Cristadoro & Lucrezia Reichlin & Giovanni Veronese, 2001. "The construction of coincident and leading indicators for the euro area business cycler of the euro area business cycle," Temi di discussione (Economic working papers) 434, Bank of Italy, Economic Research and International Relations Area.
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    5. Filippo Altissimo & Antonio Bassanetti & Riccardo Cristadoro & Mario Forni & Marco Lippi & Lucrezia Reichlin & Giovanni Veronese, 2001. "A real time coincident indicator of the euro area business cycle," Temi di discussione (Economic working papers) 436, Bank of Italy, Economic Research and International Relations Area.
    6. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    7. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    8. Hiroshi Yamada, 2012. "A Note on Band-Pass Filters Based on the Hodrick-Prescott Filter and the OECD System of Composite Leading Indicators," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2011(2), pages 105-109.
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    Cited by:

    1. Wegmüller, Philipp & Glocker, Christian & Guggia, Valentino, 2023. "Weekly economic activity: Measurement and informational content," International Journal of Forecasting, Elsevier, vol. 39(1), pages 228-243.

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    More about this item

    Keywords

    business cycles; growth cycles; composite indicators; leading indicators; principal component analysis; real-time simulations;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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