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An Alternative Approach to the Dating of Business Cycle: Nonparametric Kernel Estimation


  • Jitka Poměnková


The paper provides the methodological background for the Czech Republic business cycle dating process using an alternative approach. This approach is based on the mathematical principle of identification of extremes using estimates of derivations of time trend of the analysed time series, for which the nonparametric Gasser-Müller estimate is used. The presented methodological approach is applied on the real gross domestic product data sets, the total industry (excluding construction), the gross capital formation and the final consumption expenditure. The selected variables are taken from the national accounts system. The obtained results are compared to the widely used naive technique of business cycle dating written by Canova (1998, 1999) or Bonenkamp (2001). The presented new method specifies the identification of turning points in the business cycle dating process.

Suggested Citation

  • Jitka Poměnková, 2010. "An Alternative Approach to the Dating of Business Cycle: Nonparametric Kernel Estimation," Prague Economic Papers, University of Economics, Prague, vol. 2010(3), pages 251-272.
  • Handle: RePEc:prg:jnlpep:v:2010:y:2010:i:3:id:375:p:251-272

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    References listed on IDEAS

    1. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
    2. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.
    3. Michael Artis & Massimiliano Marcellino & Tommaso Proietti, 2004. "Characterising the Business Cycle for Accession Countries," Working Papers 261, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    4. Canova, Fabio, 1999. "Does Detrending Matter for the Determination of the Reference Cycle and the Selection of Turning Points?," Economic Journal, Royal Economic Society, vol. 109(452), pages 126-150, January.
    5. Kapounek, Svatopluk, 2009. "Estimation of the Business Cycles - Selected Methodological Problems of the Hodrick-Prescott Filter Application," MPRA Paper 27567, University Library of Munich, Germany.
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    Cited by:

    1. Sergey V. Smirnov & Nikolay V. Kondrashov & Anna V. Petronevich, 2017. "Dating Cyclical Turning Points for Russia: Formal Methods and Informal Choices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(1), pages 53-73, May.
    2. Shirly Siew-Ling WONG & Chin-Hong PUAH & Shazali ABU MANSOR & Venus Khim-Sen LIEW, 2016. "Measuring Business Cycle Fluctuations: An Alternative Precursor To Economic Crises," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(4), pages 235-248.
    3. repec:prg:jnlpep:v:2015:y:2015:i:5:id:512:p:1-18 is not listed on IDEAS
    4. Jitka Poměnková & Roman Maršálek, 2015. "Empirical Evidence of Ideal Filter Approximation: Peripheral and Selected EU Countries Application," Prague Economic Papers, University of Economics, Prague, vol. 2015(5), pages 485-502.

    More about this item


    Gasser-Müller estimate; business cycle; identification of turning points; stabilization policy;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles


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