Valuation method for land pricing based on two cumulative distribution functions

Abstract

This paper introduces the well-known valuation method based on two cumulative distribution functions (VMTCDF) that presents advantages with respect to other comparative techniques such as classical synthetic, which need a hypothesis of proportionality that is extremely simplifying and quite implausible, and econometric methods, which need databases contrary to VMTCDF that requires very little information. The VMTCDF use a single explicative variable, which summarizes in an index the different external signs that influence the market value of the asset to be assessed. The main aim of this paper is to extend the VMTCDF to find, under uncertainty, the market value of an asset from a two-dimensional vector of the characteristics of this asset. For this reason a new two-dimensional distribution is presented, Pyramidal distribution, which serves as a probabilistic model in the extended VMTCDF, and some of its statistical properties are studied. Finally, a practical application on land pricing illustrates the use of the extended VMTCDF as a tool for asset valuation. The main conclusion to be drawn from this paper is that it is the first step to extend the VMTCDF to the multidimensional case.