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Modelling phase shifts among stochastic cycles

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  • Gerhard Runstler

Abstract

Stochastic cycles are often incorporated in structural time series models to identify the cyclical components in macroeconomic time series. This paper proposes an extension of the multivariate stochastic cycle to account for phase shifts between individual cyclical components. The properties of the stochastic cycle allow phase shifts to be modelled in an entirely symmetrical way. As a result, cross correlations between cyclical components can be expressed in terms of phase shifts and phase-adjusted associations. An application demonstrates the role of phase shifts in the business cycle relationships among output, total hours worked and the real wage in the United States. Copyright Royal Economic Socciety 2004

Suggested Citation

  • Gerhard Runstler, 2004. "Modelling phase shifts among stochastic cycles," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 232-248, June.
    • Handle: RePEc:ect:emjrnl:v:7:y:2004:i:1:p:232-248
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    Cited by:

    1. Valle e Azevedo, João & Pereira, Ana, 2013. "Approximating and forecasting macroeconomic signals in real-time," International Journal of Forecasting, Elsevier, vol. 29(3), pages 479-492.
    2. Han-Liang Cheng & Nan-Kuang Chen, 2021. "A study of financial cycles and the macroeconomy in Taiwan," Empirical Economics, Springer, vol. 61(4), pages 1749-1778, October.
    3. Martyna Marczak & Víctor Gómez, 2017. "Monthly US business cycle indicators: a new multivariate approach based on a band-pass filter," Empirical Economics, Springer, vol. 52(4), pages 1379-1408, June.
    4. Matthieu Lemoine, 2006. "Annex A5 : A model of the stochastic convergence between euro area business cycles," Working Papers hal-00972793, HAL.
    5. Philippe Moës, 2012. "Multivariate models with dual cycles: implications for output gap and potential growth measurement," Empirical Economics, Springer, vol. 42(3), pages 791-818, June.
    6. Samuel Bates & Cheikh Tidiane Ndiaye, 2014. "Economic Growth from a Structural Unobserved Component Modeling: The Case of Senegal," Economics Bulletin, AccessEcon, vol. 34(2), pages 951-965.
    7. Tatiana Cesaroni & Carmine Pappalardo, 2008. "Long run and short run dynamics in italian manufacturing labour productivity," Economics Bulletin, AccessEcon, vol. 3(15), pages 1-11.
    8. Andrew Lee-Poy, 2018. "Characterizing the Canadian Financial Cycle with Frequency Filtering Approaches," Staff Analytical Notes 2018-34, Bank of Canada.
    9. Matthieu Lemoine, 2005. "A model of the stochastic convergence between business cycles," Documents de Travail de l'OFCE 2005-05, Observatoire Francais des Conjonctures Economiques (OFCE).
    10. Fabio Busetti & Michele Caivano, 2013. "The trend-cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy," Temi di discussione (Economic working papers) 941, Bank of Italy, Economic Research and International Relations Area.
    11. repec:hal:spmain:info:hdl:2441/1461 is not listed on IDEAS
    12. Guido Bulligan & Lorenzo Burlon & Davide Delle Monache & Andrea Silvestrini, 2019. "Real and financial cycles: estimates using unobserved component models for the Italian economy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 541-569, September.
    13. Marek Jarociński & Michele Lenza, 2018. "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1189-1224, September.
    14. Andrew E. Evans, 2020. "Average labour productivity dynamics over the business cycle," Empirical Economics, Springer, vol. 59(4), pages 1833-1863, October.
    15. Pierre Perron & Eduardo Zorita & Arthur P. Guillaumin & Adam M. Sykulski & Sofia C. Olhede & Jeffrey J. Early & Jonathan M. Lilly, 2017. "Analysis of Non-Stationary Modulated Time Series with Applications to Oceanographic Surface Flow Measurements," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(5), pages 668-710, September.
    16. Chen, Xiaoshan & Kontonikas, Alexandros & Montagnoli, Alberto, 2012. "Asset prices, credit and the business cycle," Economics Letters, Elsevier, vol. 117(3), pages 857-861.
    17. Claudio Borio & Piti Disyatat & Mikael Juselius, 2014. "A parsimonious approach to incorporating economic information in measures of potential output," BIS Working Papers 442, Bank for International Settlements.
    18. Philippe Moës, 2006. "The production function approach to the Belgian output gap, estimation of a multivariate structural time series model," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 49(1), pages 59-91.
    19. Philippe Moës, 2008. "Multivariate structural time series models with dual cycles : implications for measurement of output gap and potential growth," Working Paper Research 136, National Bank of Belgium.
    20. Fabio Busetti & Michele Caivano, 2016. "The trend–cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy and the Euro area," Empirical Economics, Springer, vol. 50(4), pages 1565-1587, June.
    21. Wanger, Susanne & Weigand, Roland & Zapf, Ines, 2014. "Revision der IAB-Arbeitszeitrechnung 2014 : Grundlagen, methodische Weiterentwicklungen sowie ausgewählte Ergebnisse im Rahmen der Revision der Volkswirtschaftlichen Gesamtrechnungen," IAB-Forschungsbericht 201409, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    22. João Valle e Azevedo, 2007. "A Multivariate Band-Pass Filter," Working Papers w200717, Banco de Portugal, Economics and Research Department.
    23. Lenarčič, Črt, 2021. "Estimating business and financial cycles in Slovenia," MPRA Paper 109977, University Library of Munich, Germany.

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