International Journal of Statistics and Applied Mathematics
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International Journal of Statistics and Applied Mathematics

2020, Vol. 5, Issue 4, Part C

Modelling and forecasting retail prices of maize for three agricultural markets in Tanzania


Author(s): KK Saxena and Doris Robert Mhohelo

Abstract: This study examined the modelling of maize prices using Autoregressive Integrated Moving Average (ARIMA) technique to determine the most efficient and adequate model for analyzing the maize monthly prices at the Gairo market in Morogoro Region, Manyoni market in Singida Region and Kibaigwa market in Dodoma Region. The results indicate that ARIMA (1, 1, 4) model is the most adequate and efficient model for Gairo market, ARIMA (2, 1, 3) model is the most adequate and efficient mode1 for Manyoni market and ARIMA (2, 2, 3) model is the most adequate and efficient model for Kibaigwa market. This was determined by comparing the Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) and Mean Absolute Percentage Error (MAPE). Time-series analysis was done using STATGRAPHICS, EXCEL, R software and SAS JPM. The forecast results suggest that there are expectations of increasing maize prices in Manyoni market from June-2018 to May-2019, the maize prices in Kibaigwa market are also expected to increase with time from January 2016 to December 2016 and the maize prices at Gairo market are expected to keep on increasing with time from June 2018 to May 2019. The results will make better understanding of maize prices situation and future prices will enable producers and consumers to make the right choices concerning buying and selling arrangements of Maize crop in Tanzania.

Pages: 229-245 | Views: 215 | Downloads: 9

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How to cite this article:
KK Saxena, Doris Robert Mhohelo. Modelling and forecasting retail prices of maize for three agricultural markets in Tanzania. Int J Stat Appl Math 2020;5(4):229-245.
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