Abstract:
This research used a time series model called the Seasonal Autoregressive
Integrated Moving Average (SARIMA) technique to model and forecast
wholesale prices of Tanzania`s key food crops, notably maize, rice, and beans.
The SARIMA model was selected due to its ability of ftting data with seasonality.
Monthly wholesale prices data of the three crops between February 2004
to October 2021 in Tanzania were retrieved from the website of the Bank of
Tanzania (BoT), resulting in 213 observations on each crop. The data from
February 2004 to October, 2020 were used to ft a SARIMA model and data
of November 2020 to October 2021 were used to validate the model. The
results show that SARIMA (0,1,2) (1,0,1)
12, SARIMA (0,1,0) (1,1,1)12 and SARIMA
(0,1,0) (0,1,1)
12 are the most suitable models for forecasting wholesale prices
of maize, rice and beans respectively. The model’s accuracy was tested using
Mean Absolute Percent Error (MAPE), and the results were found satisfactory.
The results reveal that maize, rice, and beans will all have higher peak prices
in February 2022, with TZS 54,083/=, TZS 167,258/=, and TZS 180,117.68/= per
100kg, respectively. Therefore, SARIMA (0,1,2)(1,0,1)12, SARIMA (0,1,0)(1,1,1)12
and SARIMA (0,1,0) (0,1,1)
12 models could serve as a useful tool for modelling
and forecasting monthly wholesale prices of maize, rice and beans respectively
in Tanzania.
