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A monthly leading indicator of Swiss GDP growth based on Okun’s law

Author

Listed:
  • Peter Kugler

    (University of Basel)

  • George Sheldon

    (University of Basel)

Abstract

We propose a unique method of nowcasting and forecasting GDP growth based on a forward-looking measure of unemployment (FLUR) and Okun’s law that offers a number of advantages over current leading indicators of the Swiss business cycle. The following investigation, covering the period from 1991/1 to 2021/4, demonstrates that our approach outperforms an AR(1) model of GDP growth equally well as the popular Business Cycle Index of the Swiss National Bank and the KOF Barometer with respect to year-to-year growth, but less so in regard to quarter-to-quarter changes. Our findings suggest that our approach offers a reliable and useful indicator to policymakers seeking easily compiled information on the current and future course of the Swiss economy at monthly time intervals.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:sjecst:v:159:y:2023:i:1:d:10.1186_s41937-023-00115-w
    DOI: 10.1186/s41937-023-00115-w
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    References listed on IDEAS

    as
    1. George Sheldon, 2020. "Unemployment in Switzerland in the wake of the Covid-19 pandemic: an intertemporal perspective," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-9, December.
    2. 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.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. Sylvia Kaufmann, 2020. "COVID-19 outbreak and beyond: the information content of registered short-time workers for GDP now- and forecasting," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-12, December.
    5. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    6. Sider, Hal, 1985. "Unemployment Duration and Incidence: 1968-82," American Economic Review, American Economic Association, vol. 75(3), pages 461-472, June.
    7. 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.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Felder, Rahel & Sheldon, George, 2023. "Ein System zur laufenden Messung der Knappheitsverhältnisse auf beruflichen Arbeitsmärkten in der Schweiz," Working papers 2023/10, Faculty of Business and Economics - University of Basel.

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    More about this item

    Keywords

    Leading indicator; Higher-frequency data; GDP growth; Unemployment; Okun’s law;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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