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Seasonality, Nonstationarity and the Structural Forecasting of the Index of Industrial Production

In: New Trends in Macroeconomics

Author

Listed:
  • Eugene Kouassi

    (University of Abidjan - Cocody)

  • Walter C. Labys

    (West Virginia University)

Abstract

Summary In this paper we focus on two STS models suitable for forecasting the index of industrial production. The first model requires that the index be transformed with a first and seasonal difference filters. The second model considers the index in its second difference filter, while seasonality is modeled with a constant and seasonal dummy variables. Tests designed to discriminate empirically between these two models are also conducted. Our results prefer the performance of the second model, particularly when the conventional ML estimation procedure is replaced by the ALS procedure. This process together with appropriate seasonal adjustment advances the possibility of using the suggested index forecasts to help to predict business cycle turning points.

Suggested Citation

  • Eugene Kouassi & Walter C. Labys, 2005. "Seasonality, Nonstationarity and the Structural Forecasting of the Index of Industrial Production," Springer Books, in: Claude Diebolt & Catherine Kyrtsou (ed.), New Trends in Macroeconomics, pages 195-221, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-28556-4_10
    DOI: 10.1007/3-540-28556-3_10
    as

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