Within the scope of real estate appraisal, the Depreciated Replacement Cost method is mostly seen as a solution of last resort, when no other option is available. Nonetheless, it is ever more useful in addressing various estimation needs. In its basic formulation, the method suffers from several simplifications that lead to rather rough results. Here we try to go beyond these limits. To this end, we propose a variant based on the following three cornerstones. The first is the partition of the replacement cost into its fundamental components, at least according to three cost items: building structure, finishes, and installations. The second cornerstone is the formulation of different depreciation curves for each of the cost items mentioned above, by processing distinct data on useful life and residual life. Finally, the third cornerstone is represented by the definition of a complex depreciation function to take into account both the original useful life of the construction and its lengthening due to partial or full refurbishments.

Purpose: Under the framework of the sales comparison approach (SCA), the sales comparison adjustment grid is among the most well-known and widely used appraisal techniques for assessing the market value of a property. Regardless, the technique application often suffers from a remarkable limitation: the marginal prices of the property attributes are seldom chosen by the appraisers based on related theories and methods; instead, that choice is recurrently based solely on their experience, which implies the marginal prices may not fully reflect the actual market appreciation for the attributes. Design/methodology/approach: Here, we propose to nest an analytic hierarchy process (AHP)-based estimation and a nonlinear optimization (NLO) method into the SCA, meant to elicit the marginal prices of the property attributes from market data and overcome the subjectivity issue inherent in SCA. Findings: In the paper, the method is worked out, and several validations are proposed, too. The SCA integrated with AHP and NLO proves to be effective in providing reliable estimates of the subjects, with minor to negligible errors primarily due to the available data structure. Originality/value: The improvement to SCA we outline here requires no additional data beyond the traditional SCA. It is meant to strengthen the somewhat shaky ground on which the technique rests, but also to be easily replicable by practitioners and appraisers using a worksheet and standard add-in packages.