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Forecasting international trade: A time series approach

Author

Listed:
  • Alexander Keck
  • Alexander Raubold
  • Alessandro Truppia

Abstract

This paper develops a time series model to forecast the growth in imports by major advanced economies in the current and following year (two to six quarters ahead). Both pure time series analysis and structural approaches that include additional predictors based on economic theory are used. Our results compare favourably with other trade forecasts, as measured by standard evaluation statistics and can serve as a benchmark for more complex macroeconomic models.

Suggested Citation

  • Alexander Keck & Alexander Raubold & Alessandro Truppia, 2010. "Forecasting international trade: A time series approach," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2009(2), pages 157-176.
    • Handle: RePEc:oec:stdkab:5ks9v44bdj32
    DOI: 10.1787/jbcma-2009-5ks9v44bdj32
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    Cited by:

    1. Sohrabpour, Vahid & Oghazi, Pejvak & Toorajipour, Reza & Nazarpour, Ali, 2021. "Export sales forecasting using artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    2. Robert Lehmann, 2021. "Forecasting exports across Europe: What are the superior survey indicators?," Empirical Economics, Springer, vol. 60(5), pages 2429-2453, May.
    3. Kamel Jlassi, 2015. "Modelling and Forecasting of Tunisian Current Account: Aggregate versus Disaggregate Approach," IHEID Working Papers 13-2015, Economics Section, The Graduate Institute of International Studies.
    4. Soheila Khajoui & Saeid Dehyadegari & Sayyed Abdolmajid Jalaee, 2023. "Forecasting exports in selected OECD countries and Iran using MLP Artificial Neural Network," Papers 2312.15535, arXiv.org.

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