Analisis de la tenencia de vivienda en el Distrito Capital

Abstract

Housing tenure is a structural element of household well-being and quality of life, and its analysis is a fundamental tool for evaluating socioeconomic conditions in urban and national contexts. From a conceptual perspective, the literature defines housing tenure as the way in which a person or household has the right to inhabit a property, whether through ownership, rental, or other forms of occupancy, such as usufruct or other forms of assignment (1). This indicator is widely used in social and economic studies, as it reflects not only the economic capacity of households but also the dynamics of the real estate market, access to credit, residential stability, and the effectiveness of public housing policies. In Colombia, the Quality of Life Survey (ECV), conducted by the National Administrative Department of Statistics (DANE), is one of the main official sources for characterizing household living conditions, including information on housing tenure (8). According to national results published by DANE, renting has become the predominant housing option in recent years. In 2023, approximately 39.5% of households owned their homes, while 40.3% rented (7). By 2024, these proportions remained relatively stable, with approximately 39.6% of households owning their homes and around 40.4% renting (6). This comparison, based on official technical bulletins, suggests a national context characterized by the persistence of renting as the dominant form of tenure and relative stability in homeownership levels. Bogotá D.C., as the country's main metropolitan area and capital, concentrates urban, economic, and demographic dynamics that tend to intensify these patterns observed at the national level. Several local studies and reports have indicated that in the city, the proportion of households living in rented accommodation exceeds that of those residing in their own homes, a phenomenon associated with factors such as high land costs, restrictions on access to mortgage credit, labor mobility, and income inequality (4). In this context, it is pertinent to specifically analyze housing tenure in Bogotá D.C. in order to understand how these dynamics manifest themselves in a highly complex urban environment. This study focuses on the analysis of housing tenure in Bogotá D.C. for the year 2024, using aggregated data by department and sex of household head from the ECV-Sex 2024 Annex. Additionally, different machine learning models are implemented and compared to identify which variables explain, within the limitations of the available dataset, the percentage of households with their own homes. Although the reference to 2023 is used only as a descriptive national context, the empirical analysis and model estimation are restricted to the year 2024, explicitly recognizing the limitations arising from the use of aggregated information and the absence of a time series.