This study aims to analyze the factors influencing rental rates in Bogotá, focusing on apartments and houses across different zones of the city. This study explores the relationship between physical property characteristics and spatial patterns affecting rental profitability.
This research uses generalized additive models (GAMs) to estimate rental rates while accounting for spatial dependencies. Data is collected from rental advertisements across Bogotá, including physical attributes and geographical coordinates. A spatial interpolation is applied to visualize rental rate behavior across the city.
The analysis reveals that the number of rooms and property age positively influence rental rates for both apartments and houses. Stratum (socioeconomic level) has an inverse relationship with profitability, especially for apartments. Built area has a positive effect for apartments but a negative one for houses. The spatial analysis shows higher rental rates on the periphery of the city, particularly in areas such as Usme and Bosa. In addition, property usage regulations in some areas affect profitability, with commercial properties having a different behavior from purely residential ones.
A limitation of this study is that the GAM framework does not explicitly model variance or temporal dynamics. Transactions not governed by contracts, and generally not published on real estate portals or advertisements, were not taken into account.
The results provide investors and urban planners with detailed spatial information to support better decision-making in Bogotá’s real estate market. The methodology can be adapted for market analysis in other cities or regions.
The findings highlight potential risks of speculative investment, displacement and inequality, helping policymakers design more inclusive housing strategies and monitor urban equity.
This research contributes to the spatial econometrics literature by applying GAM to rental market analysis, emphasizing the spatial heterogeneity of rental rates in Bogotá.
