Download:
Abstract:
It is crucial to understand the spatial effects of relevant factors on housing price variations, especially under the context of market imperfections. However, few studies have applied methods such as the hedonic price model in developing countries. This study compares both non-spatial and spatial regression models to examine the factors associated with housing prices based on the municipal housing appraisal and real estate datasets for the city of Quito, Ecuador. A set of 17 variables including structural, neighborhood and location characteristics are investigated using a traditional linear regression model and a Geographically Weighted Regression (GWR) model. The results suggest that compared to the traditional regression model, the GWR model is more effective at capturing housing market variations on a fine scale. Moreover, it reveals interesting findings on the spatial varying, sometimes opposite effects of some housing attributes on housing prices in different areas of the city, suggesting the potential impact from segregation.
Figure 2: Local R2 distribution
Citation
Valdez Gómez de la Torre, F.M. and Chen, X. (2024), “Housing price determinants in Ecuador: a spatial hedonic analysis”, International Journal of Housing Markets and Analysis, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJHMA-09-2023-0121 .
@article{VC24,
author = {Felipe Valdez and Xuwei Chen},
doi = {https://doi.org/10.1108/IJHMA-09-2023-0121},
journal = {International Journal of Housing Markets and Analysis},
number = {Issue},
pages = {XXX--YYY},
title = {Housing price determinants in Ecuador: a spatial hedonic analysis},
volume = {ahead-of-print},
year = {2024}}