I am a Lecturer (Teaching) for Latin America and the Caribbean at the UCL Jill Dando Institute of Security and Crime Science, where I contribute to designing and delivering professional development courses to police and security professionals in Latin America and the Caribbean, as well as conduct research on crime and security in the LAC region.
My research interests focus on crime in Mexico and other developing countries, especially in Latin America and the Caribbean—with particular attention to extortion against businesses and other organised crimes. My research is mainly quantitative, based on a solid analytical foundation that leverages modern advances in statistics and data science. Other interests are environmental criminology, organised crime, quantitative criminology, and repeat victimisation.
PhD in Security and Crime Science, 2020
University College London (UCL)
MRes in Security and Crime Science, 2015
University College London (UCL)
MAP (Public Administration and Public Policy), 2011
Tecnológico de Monterrey
This article focuses on the situational-, victim-, and area-level determinants of extortion compliance. Extortion, a quintessential organised crime, is one of the most common crimes in Mexico. However, compliance with extortion demands is relatively rare. Previous research suggests that compliance with extortion depends on the perceived risk of punishment for non-compliance. However, most research has been theoretical or experimental. The article offers empirical evidence of patterns of extortion compliance based on data from a large commercial victimisation survey conducted in Mexico. Findings suggest that situational factors (extortion type, presence of weapons and number of offenders) are the main determinants of extortion compliance. Victim-, and area-level variables have comparatively smaller effects. Implications for research and practice are discussed.
This study showed that the incidence of most crime types in Mexico City decreased during the COVID-19 pandemic. Furthermore, it also showed that some of the decreases were associated with the reduction of crime opportunities related to the disruption of routine activities.
Objectives. Research consistently shows that crime concentrates on a few repeatedly victimized places and targets. In this paper we examine whether the same is true for extortion against businesses. We then test whether the factors that explain the likelihood of becoming a victim of extortion also explain the number of incidents suffered by victimized businesses. The alternative is that extortion concentration is a function of event dependence.
Methods. Drawing on Mexico’s commercial victimization survey, we determine whether repeat victimization occurs by chance by comparing the observed distribution to that expected under a Poisson process. Next, we utilize a multilevel negative binomial-logit hurdle model to examine whether area- and business-level predictors of victimization are also associated with the number of repeat extortions suffered by businesses.
Results. Findings suggest that extortion is highly concentrated, and that the predictors of repeated extortion differ from those that predict the likelihood of becoming a victim of extortion. While area-level variables showed a modest association with the likelihood of extortion victimization, they were not significant predictors of repeat incidents. Similarly, most business-level variables significantly associated with victimization risk showed insignificant (and sometimes contrary) associations with victimization concentration. Overall, unexplained differences in extortion concentration at the business-level were unaffected by predictors of extortion prevalence.
Conclusions. The inconsistent associations of predictors across the hurdle components suggest that extortion prevalence and concentration are fueled by two distinct processes, an interpretation congruent with theoretical expectations regarding extortion that considers that repeats are likely fueled by a process of event dependence.