Application of ARIMA Model to Forecast Corn Prices in Mexico

Abstract

Corn is an essential grain in the Mexican culinary, cultural and social heritage. However, the volatility in corn prices brings uncertainty to agricultural farmers and has caused an increase in imports of the grain from other countries. The purpose of this study is to use time-series models regularly applied in finance to an agricultural commodity and forecast corn prices in Mexico. The study employs autoregressive integrated moving average (ARIMA) models to forecast prices in 2024 and 2025 using data on average rural prices of grain corn from the period 1980 to 2023 The results contribute to a theoretical discussion on employing statistical tools to reduce market uncertainty on agricultural commodities and provide empirical practical results on corn prices for decision making. The results are innovative in using the ARIMA statistical tool to analyze a specific commodity (corn) in a specific market (Mexico). The conclusions of the study suggest an upward trend in corn prices for 2024 and 2025, however, price stagnation and uncertainty is observed. Although government policies have introduced price guarantees for corn in Mexico, they only cover less than 3% of total production. Future studies should analyze price divergence by regions or states in Mexico.