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Forecasting US exports: An illustration using time series and econometric models

Author

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  • Mahmoud, E
  • Motwani, J
  • Rice, G

Abstract

Forecasting exports efficiently enables policy makers to plan more appropriately and thus to help to improve the US balance of trade. Exports traditionally are forecast using econometric methods. This study focuses on a comparison of various simple time series models and an econometric model. The results show that simple time series techniques can forecast exports more accurately than can an econometric model. Future emphasis needs to be placed on complementary forecasting approaches, careful data analysis and understanding of the variables and forecasting environment.

Suggested Citation

  • Mahmoud, E & Motwani, J & Rice, G, 1990. "Forecasting US exports: An illustration using time series and econometric models," Omega, Elsevier, vol. 18(4), pages 375-382.
    • Handle: RePEc:eee:jomega:v:18:y:1990:i:4:p:375-382
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    Citations

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    Cited by:

    1. Diamantopoulos, Adamantios & Winklhofer, Heidi, 2003. "Export sales forecasting by UK firms: Technique utilization and impact on forecast accuracy," Journal of Business Research, Elsevier, vol. 56(1), pages 45-54, January.
    2. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
    3. Feuerriegel, Stefan & Gordon, Julius, 2019. "News-based forecasts of macroeconomic indicators: A semantic path model for interpretable predictions," European Journal of Operational Research, Elsevier, vol. 272(1), pages 162-175.
    4. Zhao, Ze & Wang, Jianzhou & Zhao, Jing & Su, Zhongyue, 2012. "Using a Grey model optimized by Differential Evolution algorithm to forecast the per capita annual net income of rural households in China," Omega, Elsevier, vol. 40(5), pages 525-532.

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