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Modelling the Impact of Climatic Variables on Date Production in Pakistan: An ARIMAX-Based Forecasting Approach
Abstract
This study evaluates the advanced techniques to surge the accuracy of the date production forecasting in Pakistan. Employing ARIMAX models, this analysis focused on understanding and assessing the impact of fertilizer usage and climatic variables such as CO2 levels (which indirectly influence the climatic variables), temperature, and rainfall. Among the tested models, ARIMA (2,2,1) was found to be the best model and has an AIC of 673.49, a BIC of 690.11 and a log-likelihood of -328.74. Results indicated that CO₂ levels (-416.37; Std. Error: 292.90), temperature (-43.49; Std. Error: 17.43), and rainfall (-0.28; Std. Error: 0.09) had significant negative impacts on date production. Fertilizer usage had a minor positive effect (0.03; Std. Error: 0.05), which was statistically insignificant. The Ljung-Box test, Q-statistic, and Jarque-Bera test were used for a diagnostics check to validate the model's reliability. This research underscores the potential of ARIMAX/SARIMAX models to analyse trends and forecast future productions accurately and provides actionable insights for policymakers and researchers to integrate diverse ecological factors into agricultural planning, ensuring optimal resource utilisation and sustainable date production practices.
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References
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DOI: 10.33687/ijae.012.003.5364
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Copyright (c) 2024 Lutfullah Rodini, Muhammad Hanif Lakho, Velo Sutahar, Aijaz Ali Khooharo
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