A generalized method for valuing agricultural farms under uncertainty. (June 2017)

• Record Type: Journal Article
• Authors: García, C.; García, J.; López, M.M.; Salmerón, R.
• Is Part Of: Land use policy. Volume 65(2017)
• Page Start: 121
• Page End: 127
• Publication Date: 2017-06
• Subjects: C65 -- Q00 -- Q15; Farmland -- Land valuation -- Land markets -- Site factors -- Statistical uncertainty; Land use -- Periodicals; Land use -- Government policy -- Periodicals; Sol, Utilisation du -- Périodiques; Sol, Utilisation du -- Politique gouvernementale -- Périodiques; Electronic journals; 333.7305
• DOI: 10.1016/j.landusepol.2017.04.008
• Languages: English
• ISSNs: 0264-8377

Abstract

Highlights: We present the generalization of the valuation method based on the two cumulative distribution functions. It parts only from the minimum, maximum and most likely values of the asset and the external variables provided by an expert. The methodology is based on the construction of a weighted cumulative distribution function for the external variables. The example shows a main absolute relative difference between 3.92 and 4.22 with coefficient of variations lesser than one. This methodology can be applied to the valuation of agricultural farms and also to other markets with limited information. Abstract: The opacity of the farm market means that valuations are based primarily on expert estimates rather than on actual transaction prices. The valuation method based on the two cumulative distribution functions (VMTCDF), created by Ballestero (1971), improves the synthetic method based on estimating the market value of an asset by establishing a proportional relation between the asset and one external variable. However, in most cases the expert must consider multiple external variables. This paper proposes a definitive extension to k indexes with a methodology particularly applicable to the field of valuation of non-market goods or markets where little information is available as may be the case with the valuation of agricultural land. The contribution is illustrated with an empirical example.