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Seasonality, Outliers And Linearity

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  • Franses, P. H.

Abstract

In the present paper a case is made for the simultaneous treatment of seasonality, outliers and nonlinearity in economic time series. It is empirically shown that outlying observations may cause that a regularly applied differencing procedure for monthly data induces a nonlinear time series. A more appropriate handling of the eventual seasonality and nonstationarity yields that linearity can not be rejected.

Suggested Citation

  • Franses, P. H., 1990. "Seasonality, Outliers And Linearity," Econometric Institute Archives 272395, Erasmus University Rotterdam.
    • Handle: RePEc:ags:eureia:272395
    DOI: 10.22004/ag.econ.272395
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    References listed on IDEAS

    as
    1. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    2. Osborn, Denise R., 1990. "A survey of seasonality in UK macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 6(3), pages 327-336, October.
    3. Franses, P. H., 1990. "Testing For Seasonal Unit Roots In Monthly Data," Econometric Institute Archives 272393, Erasmus University Rotterdam.
    4. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
    5. Maravall, Agustin, 1983. "An Application of Nonlinear Time Series Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(1), pages 66-74, January.
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