Estimating the effect of sustainability factors on apartment prices: The case of Athens greater area

Multiple regression analysis is widely used as a research tool for modeling several aspects of both commercial and residential property. Such statistical analysis is mainly implemented for the assessment of the effect of property characteristics on values and rental prices. The aim of this paper is to estimate, through the implementation of multiple regression analysis, the impact of different environmental and sustainability characteristics on the apartment values within the wider Athens area. The relevant available literature has been thoroughly examined in order for the environmental factors which affect residential prices to be identified. The final selection of the variables of the model was determined by restrictions and limitations imposed by the nature of the factors and the availability of the data. The sample used for the statistical analysis derived from the database of Bank of Greece, which compiles all residential property valuations carried out by the Greek credit institutions. The independent variables introduced to the model are population density, infrastructure quality, building factor,compatibility of uses and built and natural environment quality. The overall explanatory power of the selected linear regression model was substantial, with the most significant independent variable being quality of built environment. Alternative models have also been attempted, though with inferior results. A number of factors with a potentially significant explanatory power have been omitted, due to the increased complexity involved in the data collection. This fact has dictated the need for further research on potential alternatives and additions to the model, which could provide with improved results.