Revisión de información y métodos estadísticos para la estimación del crecimiento predial
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Day by day are more planning and development entities that report the need for updated and accurate real estate information at different geographical levels. However, the study and analysis of property constantly faces new challenges in understanding the processes of urbanization, because in addition to presenting a hasty transformation, the environmental, social, economic or cultural factors that influence it are not clear. This makes limited the information and methodologies dedicated to knowing the evolution and transformation of property augmentation patterns and their causal elements.
In Colombia, the lack of consolidated historical data that allow the determination of property evolution at the national level, makes statistical estimation a major challenge in the country. However, the combination of information sources and the exploration of current statistical methods offers a new point of view for the usefulness of the data, this taking into account that the improvement of accuracy, usually, is achieved with the aggregation of information and the optimal selection of the estimation method.
In this sense, the Multipurpose Cadastre system is presented as a key tool, since, from its implementation, it gives the possibility of access to updated information inputs regarding the real estate market, development and territorial planning, since it aims at the integration of the real estate registry with more geographic information systems of the territory.
To address the problem in the terms discussed above, this project has as its central purpose to explore the existing data in the DANE and the other entities linked to the multipurpose cadastre; related to property quantification. Likewise, it is intended to provide disciplinary knowledge in the field of property estimation methodologies; in such a way that for future projects it allows to advance towards the modeling of incident variables in the property growth in the Colombian territory. The scanning and analysis process is done through the R and GeoDa Software