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The KOF Economic Barometer, Version 2014

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Abstract

This paper presents a composite leading indicator for the Swiss business cycle corresponding to the growth rate cycle concept. It is the result of a 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 this tradition, the calculation of the new KOF 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 Barometer six to 25 variables survived the first stage, the new - less discretionary and more automated - version of the first stage is much more generous. Currently, out of a set of 476 variables resulting in 4356 transformations thereof that are tested in the first stage, 219 variables manage to enter the second stage. The increased number of variables underlying the second stage allows a relatively stable and robust KOF Barometer - compared to its previous versions - that has hence no longer to rely on filtering techniques to reduce the noise in the final indicator. In a (pseudo-) real-time analysis the characteristics of the new KOF Barometer are compared to the previous versions and other alternatives.

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  • Klaus Abberger & Michael Graff & Boriss Siliverstovs & Jan-Egbert Sturm, 2014. "The KOF Economic Barometer, Version 2014," KOF Working papers 14-353, KOF Swiss Economic Institute, ETH Zurich.
    • Handle: RePEc:kof:wpskof:14-353
    DOI: 10.3929/ethz-a-010102658
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    Cited by:

    1. 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.
    2. Marc Burri & Daniel Kaufmann, 2020. "A daily fever curve for the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-11, December.
    3. Erhan Uluceviz & Kamil Yilmaz, 2020. "Real-financial connectedness in the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-20, December.
    4. Vera Z. Eichenauer & Ronald Indergand & Isabel Z. Martínez & Christoph Sax, 2022. "Obtaining consistent time series from Google Trends," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 694-705, April.
    5. Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2019. "Mixed-Frequency Models for Tracking Short-Term Economic Developments in Switzerland," International Journal of Central Banking, International Journal of Central Banking, vol. 15(2), pages 151-178, June.
    6. Boriss Siliverstovs, 2015. "Dissecting the purchasing managers' index," KOF Working papers 15-376, KOF Swiss Economic Institute, ETH Zurich.
    7. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
    8. Andreas Brunhart, 2019. "Der neue Konjunkturindex „KonSens“: Ein gleichlaufender, vierteljährlicher Sammelindikator für Liechtenstein," Arbeitspapiere 62, Liechtenstein-Institut.
    9. Michael Graff & Dominik Studer, 2018. "Konstruktion von Sammelindikatoren für den Konjunkturverlauf bei prekärer Datenlage am Beispiel Montenegros," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 12(3), pages 81-91, October.
    10. Peter Kugler & George Sheldon, 2023. "A monthly leading indicator of Swiss GDP growth based on Okun’s law," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-14, December.
    11. Marc Burri, 2023. "Do daily lead texts help nowcasting GDP growth?," IRENE Working Papers 23-02, IRENE Institute of Economic Research.
    12. Alain Galli, 2018. "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 179-218, November.

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    Keywords

    Business cycles; Growth rate cycles; Composite indicators; Leading indicators; Principal component analysis; Real-time simulations;
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