Abstract

HERNANDEZ HERNANDEZ, Vladimir; MAYCOTTE PANSZA, Elvira  and  QUEZADA DANIEL, Daniel. Geography of house theft in Ciudad Juárez, Chihuahua (2007-2014). Invest. Geog [online]. 2018, n.96. ISSN 2448-7279.  https://doi.org/10.14350/rig.59545.

Big cities in Mexico face significant challenges to improve their development level, including the rise in violence. This phenomenon is not unique to the Mexican context, as it can be stated that most of the major cities in the world show increased rates of violence to a greater or lesser extent. With regard to the impacts of house theft, Mexico accounts for between 15 and 18 per cent of the total number of thefts reported between 2006 and 2016, and the national survey of victimization and perception on public security (ENVIPE) indicates that this crime has a 5,028 prevalence rate at the national level.

In 2010, Ciudad Juarez reported 1,000 preliminary inquiries related to house theft; decreasing to 788 inquiries during 2013 and rising again to 908 in 2015. On average, 910 such cases were investigated 2010 to 2015. This is one of the offenses that has received little public attention, with an annual average of 910 inquiries during 2010-2015.

House theft displays a heterogeneous geographical distribution in the city, showing a high concentration in the downtown area and in some suburbs such as: Primero de Mayo, Granjas Chapultepec, Revolución Mexicana, among others. In this context, the objective of this paper is to examine the geographical relationship between the location of the house theft and features of the socio-spatial environment in Ciudad Juárez.

The working hypothesis is that house theft has can be explained largely on the geographical dimension of the environment of this phenomenon, with the criminal act concentrating on opportunities that are not random, either in time or in space. Therefore, the spatial behavior of the phenomenon should be identified considering the changes in the characteristics of the urban environment. The relationship between housing and crime has negative consequences when housing is cheap and located in less-favored areas that have been forgotten for decades. According to a literature survey, the factors that increase vulnerability include concentration of poorly-educated population, low levels of professional education, single-parent family, dependency on public assistance, poor housing, and lack of expectations and stimuli for people, but especially for the youth.

The information used on house theft corresponds to the preliminary inquiries gathered from the Secretariat of Public Security in the Municipality of Juárez and variables from the 2010 Census on General Population and Housing. For the spatial analysis, the information obtained provides the address (nearest intersection), which was used for geocoding. The correspondence between offenses and the characteristics of the urban environment was explored using a geographically weighted regression estimated using the maximum likelihood technique.

The geocoding of house theft reports yielded 2,484 events in the urban area. The distribution of this phenomenon is geographically governed by two factors: the international border and the Sierra de Juárez, which jointly determine a northwest-southeast direction. The neighborhood test evidences that significant clusters of house theft can be identified at the local level. We identified 38 high-incidence clusters of house theft and 25 high-value clusters named outliers. These results identified the variables uninhabited houses, population density, households headed by women, and concentration of young people as factors that influence house theft. The local model is adjusted to the conditions of housing development in Ciudad Juárez, characterized by large housing development units on the periphery, away from desirable conditions of accessibility to urban resources. On the other hand, there is the downtown area with high unemployment rates due to the deterioration of the area. Both cases are factors that are favorable for house theft.

Keywords : House theft; spatial pattern; geographically weighted regression; Ciudad Juarez.