Author
Listed:
- Luis Armando Galvis-Aponte
- Adriana I. Ortega-Arrieta
- Adriana M. Rivera-Zárate
Abstract
El presente documento tiene como objetivo cuantificar las diferencias en los precios de arrendamiento de vivienda entre las principales áreas metropolitanas de Colombia durante el período 2008-2024. Para ello, se construyen índices espaciales de precios tipo Fisher, que corresponden a la media geométrica de los índices de Laspeyres y Paasche. Adicionalmente, se elaboran indicadores de persistencia de estos índices con el fin de analizar la estabilidad en las jerarquías de los arrendamientos en las áreas metropolitanas. La información utilizada proviene de la Gran Encuesta Integrada de Hogares, en particular del módulo de características de la vivienda. El análisis se centra en 18 áreas metropolitanas seleccionadas de un conjunto inicial de 23, priorizando la consistencia y disponibilidad de datos durante el período de análisis. Los índices de precios se construyen a partir de modelos hedónicos aplicados a una canasta común de atributos de las viviendas, utilizando a Bogotá como ciudad de referencia. Para lograr comparaciones más robustas, se emplea el método de emparejamiento por puntaje de propensión, sintetizando así las diferencias en un único índice de precios relativo. Se observa una marcada heterogeneidad en los precios de arrendamiento. Bogotá ocupa la primera posición en la mayoría de los años analizados; sin embargo, se presentan excepciones relevantes: Cartagena lidera en 2008, 2009 y 2018, mientras que Medellín alcanza el primer lugar en 2024. Asimismo, se observa un alto grado de persistencia en las jerarquías de precios, respaldado por las altas correlaciones observadas tanto en los índices de precios como en los escalafones ocupados por las ciudades a lo largo del tiempo. **** ABSTRACT: This document aims to quantify differences in housing rental prices across the main metropolitan areas of Colombia during the 2008–2024 period. To this end, spatial price indices of the Fisher type are constructed, corresponding to the geometric mean of Laspeyres and Paasche indices. In addition, persistence indicators of these indices are developed to analyze the stability of rental cost hierarchies across metropolitan areas. The data used come from the Gran Encuesta Integrada de Hogares, specifically from the housing characteristics module. The analysis focuses on 18 metropolitan areas selected from an initial set of 23, prioritizing consistency and data availability over the 2008–2024 period. The price indices are constructed based on a common basket of housing attributes, using Bogotá as the reference city. To ensure more robust comparisons, the Propensity Score Matching method is applied, thus summarizing the differences into a single relative price index. A marked heterogeneity is observed in rental prices. Bogotá occupies the leading position in most of the years analyzed; however, there are notable exceptions: Cartagena ranks first in 2008, 2009, and 2018, while Medellín takes the lead in 2024. Moreover, a high degree of persistence is observed in the price hierarchies, supported by strong correlations of the price indices and the rank positions of the cities over time.
Suggested Citation
Luis Armando Galvis-Aponte & Adriana I. Ortega-Arrieta & Adriana M. Rivera-Zárate, 2025.
"Disparidades regionales en los precios de arrendamiento de vivienda urbana en Colombia: una evaluación empírica,"
Documentos de trabajo sobre Economía Regional y Urbana
335, Banco de la Republica de Colombia.
Handle:
RePEc:bdr:region:335
DOI: 10.32468/dtseru.335
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JEL classification:
- C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
- O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
- R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
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