A Comparison of Artificial Neural Network and Time Series Models for Forecasting GDP in Palestine

@article{Safi2016ACO,
  title={A Comparison of Artificial Neural Network and Time Series Models for Forecasting GDP in Palestine},
  author={S. Safi},
  journal={American Journal of Theoretical and Applied Statistics},
  year={2016},
  volume={5},
  pages={58}
}
  • S. Safi
  • Published 2016
  • Mathematics
  • American Journal of Theoretical and Applied Statistics
  • Time series of quarterly observations on Gross Domestic Product (GDP) is collected and used in this study. Forecasting results of ANNs are compared with those of the Autoregressive Integrated Moving Average (ARIMA) and regression as benchmark methods. Using Root Mean Square Error (RMSE), the empirical results show that ANN performs better than the traditional methods in forecasting GDP. 
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