Agricultural Combine Remaining Value Forecasting Methodology and Model (and Derived Tool)

Abstract

Harvesting is an integral component of the agricultural cycle, necessitating the use of high-performance grain harvester combines, which are utilized for a short period each year. Given the seasonality and significant cost involved, list prices ranging from a quarter to almost a million euros, a fact-based investment assessment decision-making process is essential. However, there is a paucity of research studies forecasting the remaining value of grain harvester combines in recent years. This study proposes a straightforward methodology based on public information that employs various parametric and non-parametric models to develop a robust and user-friendly model that can assist decision makers, such as farmers, contractors, sellers, and finance and insurance entities, in optimizing their harvesting operations. The model employs a power regression mode, with RMSE of 1.574 and RSqAdj of 0.8457 results, to provide accurate and reliable insights for informed decision-making. The robust model transparency enables us to easily create a mainstreamed spreadsheet-based dashboard tool.