Modeling and forecasting blackberry production in Colombia using a Box Jenkins ARIMA approach
DOI:
https://doi.org/10.17981/econcuc.44.1.2023.Econ.4Keywords:
Predictive capacity, univariate analysis, data modeling, productionAbstract
Blackberry production in Colombia contributes to the nation´s gross domestic profit, employment and farmers’ social well-being. It is considered of great economic importance as blackberry fruits are used as raw material for the agroindustry. In this manner, production instability affects farmers’ economic profitability; therefore, forecasting plays an important role in monitoring production as well as in farmers´ planting decision and resource allocation. Hence, the purpose of the study was to model and forecast blackberry production in Colombia using a Box Jenkins ARIMA approach for the period 1992-2023. A quantitative, non-experimental, correlational and descriptive research design was selected. The appropriateness of the model and its predictive capacity was assessed by verifying the different goodness-of-fit criteria. Results showed that the ARIMA (1,1,0) was the most suitable model as it captured the behavior of the actual time series. Based on the forecasted values it is expected a 5.47% increase in blackberry production for the period 2021-2023 which will consequently improve farmers´ income and thus contribute to the reduction in poverty.
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