Author(s)

Duy Quang Phung^1*, Quoc Thang Trinh², Quang Truong Do², Ngan Giang Nguyen², Van Ha Nguyen², Gia Khiem Ngo², Thi Minh Ngoc Tran²

¹Faculty of Technology and Data Science, Foreign Trade University, Hanoi, Vietnam.
²School of Economics and International Business, Foreign Trade University, Hanoi, Vietnam.

Coffee is a significant industry, accounting for 3% of Vietnam’s GDP, with annual export turnover consistently exceeding USD 3 billion. Despite global economic challenges affecting purchasing power at various times, Vietnam’s coffee exports in December 2023 continued to surge, reaching the highest level in the past 9 months at 190,000 tons, a 59.3% increase compared to November 2023, but still a slight 3.5% decrease from the same period last year. The export turnover reached USD 538 million, a 51% increase from November 2023 and a 26.4% increase from the same period last year. Therefore, forecasting the coffee export volume holds significant importance for coffee producers nationwide. This research employs the Box-Jenkins method to construct an ARIMA model for forecasting Vietnam’s coffee export volume based on annual data published by the General Statistics Office. Results indicate that among the models considered, the ARIMA(1, 1, 2) model is the most suitable. The study also provides short-term forecasts for Vietnam’s coffee export volume. However, the current model is limited to forecasting and is not yet optimized, as the assumed linearity in the model is a simplification.

ARIMA, Forecasting, Coffee Export Volume, Data Science

Phung, D. , Trinh, Q. , Do, Q. , Nguyen, N. , Nguyen, V. , Ngo, G. and Tran, T. (2024) Building the ARIMA Model for Forecasting the Production of Vietnam’s Coffee Export. Journal of Applied Mathematics and Physics, 12, 1237-1246. doi: 10.4236/jamp.2024.124076.