Public infrastructure and housing prices: An application of geographically weighted regression within the context of hedonic prices

The analysis of externalities in real state has been matter of study during the past few years. In this paper we use both conventional and spatial econometric model, as well as geographically weighted regression models, to measure the effect of the San Javier Metro Station (in Medellín, Colombia) on the housing prices of the surrounding area. The main finding of this study is that the metro station has a positive impact on the prices of houses located within a radius of 600 meter from the station. However, the railroad track accessing the station has a negative impact on housing prices located nearby.

• Autores: Duque, Juan Carlos; Velásquez Ceballos, Hermilson; Agudelo, Jorge
• Fecha de publicación: 2020
• Institución: Universidad EAFIT
• Repositorio: Repositorio EAFIT
• Idioma: spa
• OAI Identifier: oai:repository.eafit.edu.co:10784/15499
• Acceso en línea: http://hdl.handle.net/10784/15499
• Palabra clave: C21; O18; R32; Real state; GWR; Geographically Weighted Regression; Hedonic prices; Metro station; Sector Inmobiliario; GWR; Regresión Geográficamente Ponderada; Metro de Medellín; Precios hedónicos
• License: Copyright (c) 2011 Juan Carlos Duque, Hermilson Velásquez Ceballos, Jorge Agudelo