Work

Forecast Butter Prices Using ARIMA and ARIMAX Models

Year: 2026

Type: article

Abstract: This paper constructs a feasible ARIMA/ARIMAX model to forecast butter prices. The preferred model is an ARIMA (1,1,0) for the butter price series. We add exogenous control variables to reduce forecast bias, and multi-collinearity is not a problem for this forecasting objective. Based on the sample data, the mean absolute margin of error of the model is less than 4.5%, which is an acceptable bias for dairy processors seeking a reference for long-term production planning and for stakeholders developing investment plans.

Source: Journal of Applied Business and Economics

DOI: 10.33423/bng4cv30

Authors: Hongmei Jia, Yanxi Li, Cathy Zishang Liu

Institutions: East Texas A&M University, Metropolitan State University of Denver, University of Houston - Downtown

Language: English

Topic: Forecasting Techniques and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Zero hunger

Open Access status: bronze

OpenAlex ID: W7225578640

FWCI:

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