Using The ARIMA Method in Forecasting Money Supply in Libya (المجلة الدولية للبحوث العلمية, 2024)
The research paper focuses on using the Box-Jenkins methodology (ARIMA) to forecast monthly data for narrow money supply (M1) and broad money supply (M2) in Libya from January 2010 to December 2030. The study aims to determine the effectiveness of ARIMA models in long-term forecasting, considering their significant role in economic stability. The analysis revealed that the monthly time series of money supply is unstable and exhibits a general trend. To address this, the time series was converted into a stationary form to obtain the most effective models for predicting future periods. The study employed an ARIMA (0,2,2) model to predict future monthly data for M1 and an ARIMA (0,1,1) model for M2. The results indicated that ARIMA models can offer reliable short-term forecasts for money supply, but may not be suitable for long-term predictions due to external circumstances. The study recommends the use of more adaptive and dynamic models such as GARCH or SARIMA, along with improvements in data quality and the selection of variables reflecting changes or external conditions.