A SARIMA-Based Time Series Analysis of Sugar Export Quantity and Price Trends in Thailand
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This study aims to forecast trends in Thailand’s sugar export quantity and price. It uses secondary data, specifically monthly sugar export quantity and price data from January 2011 to December 2023, totaling 156 data points. The Box-Jenkins method was applied using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model, denoted as SARIMA (p,d,q)(P,D,Q)s.
Forecasting and data analysis were performed using Gretl software. The results indicate that the most appropriate forecasting models for Thailand’s sugar export quantity and price are SARIMA (1,1,1)(1,1,2)12 and SARIMA (1,1,1 (2,1,1)12, respectively. The forecast suggests that during the 2024/25 sugarcane production season, sugar export quantity is likely to increase in the initial months (January – June 2024), which aligns with the harvesting and milling season. However, from July to December 2024, export quantity is projected to decline due to the end of the harvest and the closure of sugar mills.
In terms of pricing, the forecast indicates an upward trend between July and December 2024, primarily driven by reduced export volumes, which tend to raise market prices. These trends are consistent with historical patterns, reinforcing the reliability of the SARIMA model. The findings provide practical guidance for sugarcane farmers in planning cultivation, assist industry stakeholders in optimizing production schedules, and support policymakers in formulating export and pricing strategies.
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