Agricultural Tractor Retail and Wholesale Residual Value Forecasting Model in Western Europe

Abstract

The residual value of agricultural tractors plays a pivotal role in the financial viability of agribusiness enterprises. Nevertheless, there is a dearth of comprehensive studies concerning the prognostication of both retail and wholesale residual values specific to agricultural tractors within the context of Western Europe. This research introduces an innovative methodology for assessing the residual worth of agricultural tractors, with particular consideration given to the substantial pricing discrepancies between retail and wholesale transactions. Leveraging publicly available auction data, we develop a polynomial regression model aimed at forecasting the intricate relationship between retail and wholesale residual values. Notably, the model demonstrates an exceptional robustness, surpassing previous research endeavors, as evidenced by a remarkably low root-mean-square error (RMSE) of 0.0159 and a combined adjusted coefficient of determination (RSqAdj) of 0.9997. The findings of this study offer invaluable insights into a diverse array of stakeholders, empowering them to make well-informed decisions regarding machinery specifications, investment strategies, and asset disposal choices, thereby facilitating optimal financial performance.

Keywords

• used equipment
• farm machinery
• nonparametric models
• machine learning