Incidence of crime in renting fees in Loma de Los Bernal, Medellín - 2017
DOI:
https://doi.org/10.22335/rlct.v12i2.1165Keywords:
Injuries, aggressions, crimes against people, crimes against property, economic crime, crimes against social heritageAbstract
The incidence of crime in home rentals has not traditionally been analyzed in depth in Colombia due, among other factors, to the low availability of information related to the real estate market that exists as a consequence of the low perception of security, which makes it difficult for this type of data to be available to researchers, since it is continuously kept under reserve. The main objective of this study is to establish a functional relationship between the housing rentals in the Loma de Los Bernal neighborhood in Medellín, and crimes such as theft of motorcycles and personal injuries. In addition, it also offers percentage estimates of the reduction in the value of home rentals as a result of the commission of these crimes. The technique used was that of geographically weighted regressions. With this procedure it is possible to obtain results with higher levels of adjustment when compared with other methodologies, thanks to the fact that it allows to spatially weight all of the data obtained from the Real Estate Market of Medellín and Antioquia, as well as from the portal datosabiertos.gov.co. The main revelation of this work includes finding mathematical evidence that personal injuries and theft of motorcycles deteriorate the housing rental market in the Loma de Los Bernal neighborhood and tend to reduce the willingness of potential tenants to pay by 0.77% and 2.77%, respectively, with which these crimes constitute negative externalities that affect the well-being of society.
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References
Agudelo, J., Duque, J., & Velásquez, H. (2011). Infraestructura pública y precios de vivienda: una aplicación de regresión geográficamente ponderada en el contexto de precios hedónicos. Ecos de Economía, 15(33), 95-122.
Agudelo, J., & Ospina, O. (2020). Property valuation using threedimensional probability distributions. Medellín: Optimal Books.
Agudelo, K., & Martínez, D. (2020). International economics a mathematical approach. Medellín: Optimal Books.
Anselin, L. (1988). Spatial econometrics: methods and models. Dordrecht: Kluwer Academic Publishers.
Basu, S., & Thibodeau, T. (1998). Analysis of spatial autocorrelation in house prices. Journal of Real Estate Finance and Economics, 17, 61-85.
Beaty, J. (1952). Rental real estate often a good investment. Journal of Medical Economics, 5(6), 93-94.
Bitter, C., Mulligan, G., & Dall’erba, S. (2006). Incorporating spatial variation in housing attribute prices: a comparison of geographically weighted regression and the spatial expansion method. Journal of Geographical Systems, 9(1), 7-27.
Buonanno, P., Montolio, D., & Raya-Vílchez, P. (2013). Housing prices and crime perception. Empirical Economics, 45(1), 305-321.
Burnell, J. (1988). Crime and racial composition in contiguous communities as negative externalities. American Journal of Economics and Sociology, 47, 177-193.
Can, A. (1992). Specification and estimation of hedonic house price models. Regional Sciences and Urban Economics, 22, 453-474.
Chasco, C. (2003). Econometría espacial aplicada a la predicción extrapolación de datos microterritoriales. Madrid: Consejería de Economía e Innovación Tecnológica. Comunidad de Madrid.
Dewey, L. & DeTuro, P. (1950). Should I invest in real estate? Journal of Medical Economics, 28(3), 85-93.
Fotheringham, A., Brunsdon, C. & Charlton, M. (2002). Geographically weighted regression: the analysis of spatially varying relationship. West Sussex, GB: John Wiley and Sons.
Lancaster, K. (1966). A new approach to consumer theory. Journal of Political Economy, 74(1), 132-157.
Naroff, J., Hellman, D., & Skinner D. (1980). The Boston experience: estimates of the impact of crime on property values. Growth Change, 11, 24-30.
Martínez, D., & Agudelo, K. (2020). Basic econometrics a mathematical approach, Medellín: Optimal Books.
Martínez, D., & Ospina, O. (2020). Financial instruments a mathematical approach. Medellín: Optimal Books.
Martínez, D., & Ospina, O. (2018). Incidencia de las pandillas en los cánones de arrendamiento de vivienda en Medellín durante 2015. Revista Espacios, 39(13).
Ospina, O., & Agudelo, J. (2020). Infrastructure and lease market in Medellín an analysis using geographically weighted regressions. Colombia: Optimal Books.
Rizzo, M. (1979). The effect of crime on residential rents and property values. The American Economist. 23(1), 16-21.
Rosen, S. (1974). Hedonic prices and implicit markets: product differentiation and pure competition. Journal of Political Economy. 82, 34-55.
Yu, D. (2004). Modeling housing market dynamics in the city of Milwaukee: a geographically weighted regression aproach. Recuperado de http://www.ucgis. org/ucgisfall2004/studentpapers/files/danlinyu.pdf
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