Hedonic valuation of urban attributes on Medellin’s housing prices

Colombia’s second largest city, Medellin, has transformed itself over the last two decades to become a model for social and sustainable urban development. After suffering deep crisis during the decades of 70’s and 80’s due to economic and social factors, the urban and city transformation is remarkable. Medellín has opted to use the architecture and urbanism as a tool for social development, redressing deep and long-standing social and spatial imbalances. Medellín’s urban change involve a comprehensive strategy that seek solutions to mobility, governance and education together with recovery of public space and green areas. The city has developed law-enforcement initiatives and making a series of innovative, public investment, such as urban gondolas and hillside electrical escalators, designed to integrate the city’s low – income residents and communities with its wealthier commercial center (Rodin, 2014). This study attempt to measure the implicit price of urban attributes in determining housing values of Medellín. We assess the extent to which neighborhood and locational characteristics may affect the marginal willingness to pay (MWTP) using a sample of over 11.000 individual houses based in city’s cadastral data for 2011. Our study take an explicit spatial econometrics perspective. We account for spatial dependence and endogeneity using S2SLS and GS2SLS estimations (Kelejian and Prucha, 1998, 1999) and also for spatial heterogeneity (heteroskedasticity in the error terms) using Kelejian Prucha HAC estimator and GS2SLS – HET. We found that urban land mixture, locate far from Metro cable and equipments have a positive impact over housing prices, while houses far from main roads suffer a negative effect on their prices. Furthermore, distance from Metro, downtown and BRT stations do not have a homogeneous impact over housing, such that, we did not get conclusive MWTP estimations respect to those urban attributes. Neighborhood features as population density and socio-economic stratum have the expected impact, in this sense, more populated and poor neighborhoods present the lower housing prices while those with opposite features have higher housing prices. In the same line, neighborhoods with higher rate of people with college degree present higher values over same with lower with educated people. Finally, we do not find evidence about the impact of presence of elder and black people.