Predicting the Residual Value of Heavy Construction Equipment

TLDR: This paper argues that the residual value can be predicted accurately based on publicly accessible data from equipment auctions and publications by manufacturers and their distributors based on multi-linear regression analysis.

Abstract: Heavy construction equipment is routinely used on construction projects that entail earthmoving operations. Owning and operating these machines may comprise a significant portion of the project costs. An important element of the owning costs is the residual value. However, the nature of the residual value of construction equipment is largely unknown. Ongoing research at Virginia Tech examines the residual value of different types of construction equipment to provide a better approach than the rules of thumb currently used by equipment managers. This paper argues that the residual value can be predicted accurately based on publicly accessible data from equipment auctions and publications by manufacturers and their distributors. Related research in agriculture and forestry is reviewed. Data collection and preparation and results from the multi-linear regression analysis are described. Statistical measures of the goodness-of-fit for different possible functional forms of the regression model are given and a sample calculation is presented.