Incidencias de las economías de aglomeración en la productividad territorial : caso de estudio en la Localidad de Chapinero mediante análisis de datos espaciales: 2013-2017
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Through knowledge of the behaviors and capacities of a territory (Llanos, 2018), better ways to manage policies and strategies that promote the development and well-being of cities can be determined (Mendoza & Capo, 2017). In recent years, the development of the territory has become an object of great interest to its stakeholders due to the introduction of spatial aspects in an economic sphere, which allows a city to recognize internal and external factors (Bateman & Martínez, 2011) susceptible to changes in terms of competitiveness.
This research proposal is formulated with the aim of proposing and developing a model based on Spatial Data Analysis that allows measuring the behavior of business dynamics generated in 19 economic sectors of the productive fabric of the town of Chapinero in the city of Bogotá D.C. and explain their location patterns and geographic concentration.
The methodology used is oriented, first, to characterize the existing business typology in the town of Chapinero through two approaches: (1) analyze the Zonal Planning Units (hereinafter UPZ) belonging to the town of Chapinero and define the business dynamics that presents each UPZ at the level of sectoral distribution and economic development. (2) analyze the financial situation of the economic sectors during the 2013-2017 period present in the town, its variations in terms such as working capital and debt level, among others.
In the next stage, the study of agglomeration economies based on partitioned clustering techniques begins, combining Principal Component Analysis (PCA) and the K-means method, which are multivariate analysis techniques for data with multiple continuous variables and that They allow to measure the behavior of business dynamics generated in different economic sectors of the productive fabric of the Chapinero locality. At this stage it is not interesting to analyze agglomerations from the geographical aspect (neighborhood), but it is interesting to identify and understand which economic sectors have developed related strategies (during the years 2013-2017), focused on leverage from assets, liabilities, equity and their relationship with net profits.
The next level of analysis is geographic, and seeks to develop an analysis from localization economies or urbanization economies (Duranton & Puga, 2004), allowing to define by means of the Ripley function k if there are agglomerations of an industrial nature present in the locality, understood this such as the concentration of activity (similar processes) in a particular sector (Rosenthal & Strange, 2004). It is interesting to know if this concentration is given by the relations and the geographical logics of the productive organization. The objective is to estimate whether business units installed in the locality are benefiting from the agglomeration economies, if there is a difference between sectors with or without agglomeration.