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Forecasting of vegetable area, production, and productivity of Nepal was made from the historical data of 1977/78 to 2019/20 by using the Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) models. The best fitted ARIMA models were chosen based on the minimum value of the selection criterion, Akaike information criteria (AIC) and Bayesian information criteria (BIC). ARIMA (0, 2, 1) model was found suitable for all areas and production, whereas ARIMA (0, 2, 0) model was best fitted for forecasting vegetable productivity. The model was cross-validated by comparing the point prediction with the actual test series data from 2015/16 to 2019/20. The performances of models were determined from the mean absolute percent error (MAPE) value. The MAPE was found to be 2.70%, 2.40%, and 3.80%, respectively for the prediction of area, production, and productivity. The forecast was made for the immediate five years (2020/21 to 2024/25), and it showed an increasing value for area and production while the forecasts of productivity had lower values. The vegetable production policy in Nepal should be planned following accurate forecasts to increase production in the upcoming years. Awareness among the vegetable growers should be raised in the following years with appropriate extension programs. Author Biography Shivahari Devkota, Department of Agricultural Economics and Agribusiness Management, Faculty of Agriculture, Agriculture and Forestry University, Chitwan Department of Agricultural Economics and Agribusiness Management, Faculty of Agriculture Downloads PDF Published 28-02-2022 How to Cite Thapa, R., Devkota, S., Subedi, S., & Jamshidi, B. (2022). Forecasting Area, Production and Productivity of Vegetable Crops in Nepal using the Box-Jenkins ARIMA Model. Turkish Journal of Agriculture - Food Science and Technology, 10(2), 174–181. https://doi.org/10.24925/turjaf.v10i2.174-181.4618 More Citation Formats ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX Issue Vol. 10 No. 2 (2022) Section Research Paper License

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