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Testing for seasonal unit roots in monthly panels of time series

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  • Kunst, R.M.
  • Franses, Ph.H.B.F.

Abstract

We consider the problem of testing for seasonal unit roots in monthly panel data. To this aim, we generalize the quarterly CHEGY test to the monthly case. This parametric test is contrasted with a new nonparametric test, which is the panel counterpart to the univariate RURS test that relies on counting extrema in time series. All methods are applied to an empirical data set on tourism in Austrian provinces. The power properties of the tests are evaluated in simulation experiments that are tuned to the tourism data.

Suggested Citation

  • Kunst, R.M. & Franses, Ph.H.B.F., 2009. "Testing for seasonal unit roots in monthly panels of time series," Econometric Institute Research Papers EI 2009-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:14861
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    Cited by:

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    3. Cáceres Hernández, J.J., 2001. "Optimalidad del patrón estacional de las exportaciones canarias de tomate," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 18, pages 41-66, Agosto.
    4. Kunst, Robert M., 2014. "A Combined Nonparametric Test for Seasonal Unit Roots," Economics Series 303, Institute for Advanced Studies.
    5. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex Business School.

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    More about this item

    Keywords

    nonparametric test; panel; seasonality; tourism; unit roots;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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