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Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model

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  • Alain Galli

    (Swiss National Bank)

Abstract

For policy institutions such as central banks, it is important to have a timely and accurate measure of past and current economic activity and the business cycle situation. The most prominent example for such a measure is gross domestic product (GDP). However, GDP is only released at a quarterly frequency and with a substantial delay. Furthermore, it captures elements that are not directly linked to the business cycle and the underlying momentum of the economy. In this paper, I construct a new business cycle index for the Swiss economy, which uses state-of-the-art methods, is available at a monthly frequency and can be calculated in real-time, even when some indicators are not yet available for the most recent periods. The index is based on a large and broad set of monthly and quarterly indicators. As I show, for the case of Switzerland, it is important to base a business cycle index on a broad set of indicators instead of only a small subset. This result confirms the findings of a previous study on tracking short-term economic developments in Switzerland and is in contrast with the results for other countries.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:jbuscr:v:14:y:2018:i:2:d:10.1007_s41549-018-0030-4
    DOI: 10.1007/s41549-018-0030-4
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    Cited by:

    1. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    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. Simon Beyeler, 2019. "Streamlining Time-varying VAR with a Factor Structure in the Parameters," Working Papers 19.03, Swiss National Bank, Study Center Gerzensee.
    4. Christian Glocker & Philipp Wegmueller, 2020. "Business cycle dating and forecasting with real-time Swiss GDP data," Empirical Economics, Springer, vol. 58(1), pages 73-105, January.
    5. Lucas Marc Fuhrer & Basil Guggenheim & Matthias Jüttner, 2019. "A survey-based estimation of the Swiss franc forward term premium," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 155(1), pages 1-18, December.
    6. 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.
    7. Agnieszka Gehringer & Thomas Mayer, 2021. "Measuring the Business Cycle Chronology with a Novel Business Cycle Indicator for Germany," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 71-89, April.

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    More about this item

    Keywords

    Business cycle index; Dynamic factor model; Mixed frequency; Switzerland;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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