Assessing the Impact of Urban Improvement on Housing Values: A Hedonic Pricing and Multi-Attribute Analysis Model for the Historic Centre of Venice
30.11.2017
Paolo Rosato (Department of Engineering and Architecture – University of Trieste); Margaretha Breil (Fondazione Eni Enrico Mattei); Carlo Giupponi ( Department of Economics – Ca’ Foscari University); Raul Berto (Department of Engineering and Architecture – University of Trieste)
Buildings 2017, 7(4), 112; https://doi.org/10.3390/buildings7040112
The Hedonic Pricing Method is one of the principal assessment methods
for evaluating services and resources not normally exchanged on the
market. However, the method is often unable to account for the great
variety of qualities in an urban context and faces scarce and
heterogeneous market data. This paper presents a model for the valuation
of benefits generated by environmental and urban improvement
investments adopting a mixed hedonic- multi-attribute procedure for
modeling a value function of urban real estate values. The peculiarity
of the model is that the independent variables are aggregated
indicators, which synthetize more detailed characteristics. Using the
expertise of real estate agents, all relevant variables influencing
real estate values were weighted and synthetized in a set of cardinal
indicators. Next, market prices were used to calibrate a hedonic
function that transforms the cardinal indicators into real estate
values. The valuation model was integrated into a GIS for mapping the
housing value, and its variation induced by urban investment. The
proposed model pointed out plausible and robust results, in particular,
the possibility to use any available information, such as location,
position, technical and economic characteristics of buildings, and
organize it in a flexible and transparent way, and to keep evident the
role of each characteristic through the hierarchical structure of the
model. The model was applied to the real estate market of Venice to
test the effects of the MOSE project (Electromechanical Experimental
Module) for the protection of Venice from high tides. The results of
the application showed a relevant increase in real estate values in the
center of Venice, especially related to property in ground floor
units, of about 1.4 billion Euros.
The Hedonic Pricing Method is one of the principal assessment methods for evaluating services and resources not normally exchanged on the market. However, the method is often unable to account for the great variety of qualities in an urban context and faces scarce and heterogeneous market data. This paper presents a model for the valuation of benefits generated by environmental and urban improvement investments adopting a mixed hedonic- multi-attribute procedure for modeling a value function of urban real estate values. The peculiarity of the model is that the independent variables are aggregated indicators, which synthetize more detailed characteristics. Using the expertise of real estate agents, all relevant variables influencing real estate values were weighted and synthetized in a set of cardinal indicators. Next, market prices were used to calibrate a hedonic function that transforms the cardinal indicators into real estate values. The valuation model was integrated into a GIS for mapping the housing value, and its variation induced by urban investment. The proposed model pointed out plausible and robust results, in particular, the possibility to use any available information, such as location, position, technical and economic characteristics of buildings, and organize it in a flexible and transparent way, and to keep evident the role of each characteristic through the hierarchical structure of the model. The model was applied to the real estate market of Venice to test the effects of the MOSE project (Electromechanical Experimental Module) for the protection of Venice from high tides. The results of the application showed a relevant increase in real estate values in the center of Venice, especially related to property in ground floor units, of about 1.4 billion Euros.