Unfolding the potential of the ARIMA model in forecasting maize production in Tanzania
Purpose – This paper was set to develop a model for forecasting maize production in Tanzania using the autoregressive integrated moving average (ARIMA) approach. The aim is to forecast future production of maize for the next 10 years to help identify the population at risk of food insecurity and qua...
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| Auteurs principaux: | , |
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| Format: | Article |
| Langue: | en_US |
| Publié: |
Business Analyst Journal (Emerald Publishing Limited )
2024
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| Sujets: | |
| Accès en ligne: | https://scholar.mzumbe.ac.tz/handle/123456789/377 |
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| Résumé: | Purpose – This paper was set to develop a model for forecasting maize production in Tanzania using the
autoregressive integrated moving average (ARIMA) approach. The aim is to forecast future production of maize for
the next 10 years to help identify the population at risk of food insecurity and quantify the anticipatedmaize shortage.
Design/methodology/approach – Annual historical data on maize production (hg/ha) from 1961 to 2021
obtained from the FAOSTAT database were used. The ARIMA method is a robust framework for forecasting
time-series data with non-seasonal components. The model was selected based on the Akaike Information
Criteria corrected (AICc) minimum values and maximum log-likelihood. Model adequacy was checked using
plots of residuals and the Ljung-Box test.
Findings – The results suggest that ARIMA (1,1,1) is the most suitable model to forecast maize production in
Tanzania. The selected model proved efficient in forecasting maize production in the coming years and is
recommended for application.
Originality/value – The study used partially processed secondary data to fit for Time series analysis using
ARIMA (1,1,1) and hence reliable and conclusive results |
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