This research aimed to develop an ARIMA(1,0,11) model for forecasting inflation rates in Kenya. The research utilized historical inflation data from January 2005 to August 2022 to develop the model and evaluated its performance on a test set spanning from September 2022 to August 2023. The results demonstrated that the ARIMA model provided accurate forecasts, with low forecast errors in terms of MSE, RMSE, MAE, and MAPE. These forecasts have practical utility for various stakeholders, including policymakers, businesses, and financial institutions, as they can use the information to inform pricing strategies, interest rate policies, and other economic decisions. Additionally, the study highlighted the importance of data quality, continuous monitoring of economic factors, and periodic model refinement to ensure the effectiveness of inflation forecasting in a dynamic economic environment.
Keywords: Arima model, Forecasting, Kenya, Modelling, inflation rates
