A House Price Modeling Based on Clustering and Kriging: The Medellín Case

In this study, house prices are modeled using a mixed two-stage model for mass appraisal employing valuations of second-hand housing units conducted in Medellín, Colombia. the first stage, submarkets houses that share non-spatial attributes created clustering; second spatial dependency is incorporated into price estimation kriging. The best results were obtained when sample was divided three property area and age as classification criterion later applying Matérn kriging to submarket 1, spherical 2, circular 3. These may provide further guidance enhance practice other Latin American cities well potentially developing countries.