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FORECASTING THE CONSUMER PRICE INDEX USING A SARIMA MODEL WITH GARCH INNOVATIONS: THE CASE OF CÔTE D’IVOIRE
Keywords:
consumer price index, time series, SARIMA, hybrid SARIMA-GARCH, SARIMA-GARCH meta-modelDOI:
https://doi.org/10.17654/0972086325018Abstract
The monthly Consumer Price Index (CPI) of Côte d’Ivoire is modeled to improve short-term inflation monitoring and forecasting. A seasonal ARIMA specification is first identified, and volatility clustering in the residuals is then addressed with a GARCH component. Model selection is guided by AIC/BIC, while forecast accuracy is assessed using RMSE, MAE, MAPE and TIC. The preferred linear specification is residual diagnostics indicate conditional heteroscedasticity, for which a variance process is adopted. Three strategies are evaluated baseline SARIMA, hybrid SARIMA-GARCH, and a SARIMA-GARCH meta-model showing that incorporating conditional variance dynamics materially enhances forecast performance. The rolling-windows hybrid provides the most accurate out of sample predictions. These results underscore the value of combining seasonal linear structure with volatility modeling for CPI series in emerging economies and provide a practical tool for policymakers tasked with inflation surveillance and price stability decisions.
Received: September 12, 2025
Revised: October 12, 2025
Accepted: October 25, 2025
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