An Application of Time Series ARIMA Forecasting Model for Predicting Tobacco Production in Zimbabwe

Tichaona W. Mapuwei^1, , Jenias Ndava², Mellissa Kachaka¹ and Brain Kusotera¹

¹Department of Statistics and Mathematics, Bindura University of Science Education, Bindura, Zimbabwe

²Department of Biological Sciences, Bindura University of Science Education, Bindura, Zimbabwe

Cite this paper:
Tichaona W. Mapuwei, Jenias Ndava, Mellissa Kachaka and Brain Kusotera. An Application of Time Series ARIMA Forecasting Model for Predicting Tobacco Production in Zimbabwe. American Journal of Modeling and Optimization. 2022; 9(1):15-22. doi: 10.12691/ajmo-9-1-3

Abstract

Tobacco has been the backbone of Zimbabwe’s agricultural economy since long and ranks second most important cash crop after food crops. Of late, tobacco yield has been diminishing in Zimbabwe. A systematic study of tobacco yield was adopted to formulate appropriate strategies to address this diminishing trend. The researchers focused on time series analysis of tobacco yield (1980-2018) using autoregressive integrated moving average (ARIMA) models to forecast 2019-2023 yield. The ARIMA model showed that production of tobacco would be 1511.78 kg/hectare by end of 2023. The researchers assumed that total tobacco yield reflects the estimated total national production in Zimbabwe. The study employed Box-Jenkins methodology in building the ARIMA model. Data analysis was conducted using R-software, and ARIMA (1, 1, 0) was identified as best model. Model diagnostics were performed to ensure validity. Total yield predicted, displayed a downward slope characterised by slight changes on the overall decreasing slope during the forecasted years. The success of higher area and productivity lies in timely provision of adequate inputs, educating and training of farmers, soil conservation and reclamation, and supportive government policies regarding tobacco production. Further studies should consider qualitative approaches with relevant key stakeholders to solicit information behind the observed trends.

Keywords:
Tobacco production time series analysis ARIMA forecasting Zimbabwe

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