Comparative analysis of private sector financing forecasting in Algeria: Empirical approaches using exponential smoothing and ARIMA models
Keywords:
Algeria, private-sector financing, exponential smoothing, ARIMA modellingAbstract
This article conducts a forecasting analysis of private-sector financing in Algeria based on two distinct methods. The time series studied is the share (% of GDP) of credit allocated to the private sector, covering the annual period from 1964 to 2023. The two forecasting methods employed are exponential smoothing and ARIMA modelling. The results show that the forecasting method by exponential smoothing provides stable forecasts in the short and/or medium term by underestimating major economic shocks. In contrast, the ARIMA approach generates more dynamic forecasts, effectively capturing unpredictable variations. Theoretically, the financial analysis is guided by the works of Box and Jenkins on ARIMA modelling, highlighting the adaptability and precision of this method for adjusting economic policies. In conclusion, combining the two approaches would allow for a more robust evaluation of private-sector financing in Algeria while emphasising the importance of accurate data for reliable economic forecasting.
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