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Bayesian Analysis of Seasonal Unit Roots and Seasonal Mean Shifts

Author

Listed:
  • Franses, Ph.H.B.F.
  • Hoek, H.
  • Paap, R.

Abstract

In this paper we propose a Bayesian analysis of seasonal unit roots in quarterly observed time series. Seasonal unit root processes are useful to describe economic series with changing seasonal fluctuations. A natural alternative model for similar purposes contains deterministic seasonal mean shifts instead of seasonal stochastic trends. This leads to analysing seasonal unit roots in the presence of mean shifts using Bayesian techniques. Our method is illustrated using several simulated and empirical data.

Suggested Citation

  • Franses, Ph.H.B.F. & Hoek, H. & Paap, R., 1995. "Bayesian Analysis of Seasonal Unit Roots and Seasonal Mean Shifts," Econometric Institute Research Papers EI 9527-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1354
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    2. Swanson, Norman R. & Urbach, Richard, 2015. "Prediction and simulation using simple models characterized by nonstationarity and seasonality," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 312-323.
    3. Uwe Hassler & Paulo M. M. Rodrigues, 2004. "Seasonal Unit Root Tests Under Structural Breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(1), pages 33-53, January.
    4. Raimundo Soto, 2002. "Ajuste Estacional e Integración en Variables Macroeconómicas," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 39(116), pages 135-155.
    5. Franses, Philip Hans & van Dijk, Dick, 2005. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," International Journal of Forecasting, Elsevier, vol. 21(1), pages 87-102.
    6. Mickael Salabasis & Sune Karlsson, 2004. "Seasonality, Cycles and Unit Roots," Econometric Society 2004 Australasian Meetings 268, Econometric Society.
    7. Harvey, David I. & Leybourne, Stephen J. & Newbold, Paul, 2002. "Seasonal unit root tests with seasonal mean shifts," Economics Letters, Elsevier, vol. 76(2), pages 295-302, July.
    8. Artur C. B. da Silva Lopes & Antonio Montanes, 2005. "The Behavior Of Hegy Tests For Quarterly Time Series With Seasonal Mean Shifts," Econometric Reviews, Taylor & Francis Journals, vol. 24(1), pages 83-108.
    9. Alexander Vosseler & Enzo Weber, 2017. "Bayesian analysis of periodic unit roots in the presence of a break," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3841-3862, August.
    10. Christiano, Lawrence J. & Todd, Richard M., 2002. "The conventional treatment of seasonality in business cycle analysis: does it create distortions?," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 335-364, March.
    11. Kunst, Robert M., 1997. "Decision Bounds for Data-Admissible Seasonal Models," Economics Series 51, Institute for Advanced Studies.
    12. Rolando Gonzales Martínez, 2012. "Bayesian seasonal analysis with robust priors," Investigación & Desarrollo, Universidad Privada Boliviana, vol. 1(12), pages 33-38.
    13. Carmine Pappalardo & Gianfranco Piras, 2004. "Vector-Autoregression Approach to Forecast Italian Imports," ISAE Working Papers 42, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    14. Paap, Richard & Franses, Philip Hans & Hoek, Henk, 1997. "Mean shifts, unit roots and forecasting seasonal time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 357-368, September.

    More about this item

    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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