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Improving the accuracy of forecasting macroeconomic indicators in Iraq using artificial intelligence compared to traditional models | ||
| AL-Qadisiyah Journal For Administrative and Economic sciences | ||
| Volume 28, Issue 1, April 2026, Pages 140-160 PDF (2.56 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.33916/qjae.2026.01140160 | ||
| Authors | ||
| Sanaa Ali Jabber; Miqdad Jassim Abd; Wadhah R. Rahi; Jehan kassam sahib | ||
| University of Al-Muthanna | ||
| Abstract | ||
| The study aimed to demonstrate the extent to which artificial intelligence models can improve the accuracy of forecasting macroeconomic indicators compared to the traditional model used in analyzing these indicators in Iraq for the period 1990-2024. The variables or economic indicators included (GDP, inflation, oil price, exchange rate). The time series was tested for stationarity to apply the ARIMA model compared to artificial intelligence models LSTM and Transformer. Better results were obtained using artificial intelligence models compared to the traditional ARIMA model for all economic indicators. The study recommends the possibility of adopting the artificial model in forecasting instead of traditional models in decision-making and shaping future policies related to the economic aspect of Iraq. | ||
| Keywords | ||
| forecasting; economic indicators; LSTM; ARIMA; Transformer | ||
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