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Combining forecasts to enhance fish production prediction: the Case of Coastal Fish Production in Morocco

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  • David Bouras

    (Lincoln University, Missouri, EEUU.)

Abstract

This paper seeks to enhance forecast accuracy by combining three individual forecasting models. These models include: the Autoregressive Integrated Moving Average model (ARIMA), the Generalized Autoregressive Conditional Heteroscedastic model (GARCH), and the Census X11 model. Applied to the Moroccan coastal fish production, the empirical results show that in terms of predictive ability the composite model outperforms the individual forecasting models. In addition, the results reveal that the forecast accuracy gains arising from combining the individual forecasts range from nearly 8% to over 95%.

Suggested Citation

  • David Bouras, 2015. "Combining forecasts to enhance fish production prediction: the Case of Coastal Fish Production in Morocco," Economic Analysis Working Papers (2002-2010). Atlantic Review of Economics (2011-2016), Colexio de Economistas de A Coruña, Spain and Fundación Una Galicia Moderna, vol. 1, pages 1-1, December.
    • Handle: RePEc:eac:articl:10/14
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    References listed on IDEAS

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