A Comparative Study of ARIMA and Holt-Winters Exponential Smoothing Models for Rice Price Forecasting in Tanzania

Abstract

Time series models are promising tools for forecasting commodity prices. However, their applications to guide producers in agricultural investments and marketing decisions are still limited. This article compares the ARIMA and Holt-Winters Exponential Smoothing models in terms of forecasting the monthly wholesale rice price in Tanzania. Even with very little difference, the Holt-Winters additive model showed the best results for forecasting rice prices compared to the ARIMA model. Thus, both models can be used to forecast the prices of agricultural products.