The interaction between land use and transportation infrastructure is a topic that has been extensively researched and continues to be of interest as new underlying economic, infrastructure and environmental conditions emerge. In this research, the direct and indirect effects of transportation infrastructure and policies on house prices and rents are studied. Since real estate transaction data are not available, a web-scraping tool was developed to parse house prices and attributes from publicly available resources. Econometric models of two categories were then estimated: (1) hedonic price models, based on Ordinary Least Squares (OLS) and (2) spatial econometric models, such as the spatial regression model (SAR), spatial error (SEM), Durbin (SDM) and autocorrelation (SAC) model and Geographically Weighted Regression (GWR), which are increasingly used by econometricians in order to capture the effect of the - usually unobserved - spatial factors on house valuation. The results of this research indicate that proximity to transportation infrastructure has a direct impact on house and apartment purchase prices and rents, which is either positive or negative depending on the type of the transportation system. Metro, tram, suburban railway and bus stations affect the prices positively, while ISAP (the old urban railway of Attica) and national rail stations, airports and ports, have a negative effect, due to a number of externalities associated with them, such as noise. The obtained results are consistent with expectations and the literature. While these results cannot be assumed directly transferable to other locations and areas, they could be cautiously used as indications for planning applications (where dedicated models have not been developed). (C) 2013 Elsevier Ltd. All rights reserved.