Post carbon city and real estate market: Testing the dataset of reggio calabria market using spline smoothing semiparametric method

In this paper a hedonic price function built through a semiparametric additive model is tried out for the real estate market analysis of the central area of Reggio Calabria. The semiparametric model uses Penalized Spline functions and aims to achieve an improvement in the prediction of the market prices of housing properties in the central area of Reggio Calabria. More in particular, the final objective of the research is to detect and to identify possible potential market premium in real estate exchange and rent markets for green buildings. This is the first preliminary phase for the unavoidable verification of the robustness of the real estate sample, or for the subsequent individuation of progressive real estate sub-samples