This study examines determinants of leftist violence at the municipal level in Colombia from 2000 through 2010. A multilevel GLMM model with a negative binomial distribution is used to take advantage of the information available at the municipal and department level. Surprisingly, inequality was not a significant covariate of violence, and agricultural GDP tended to reduce, instead of increase, guerrilla violence. The main risk factors identified include physical characteristics such as rugged topography and prior violence, but also factors that are candidates for policy action, such as unemployment, incorporation of the poor into public services, repression, and the energy and mining sector. These findings suggest interventions to decrease risks of guerrilla violence beyond merely strengthening the state. While repression tends to escalate violence, targeted policies to provide health benefits to those currently underserved, and securing mining and oil operations can effectively reduce the risk of violence.

Although Colombia is well known for its persistent leftist guerrilla conflict, the country also suffers from paramilitary violence. This study examines the potential factors related to persistent paramilitary violence in the form of human rights violations. How has paramilitary activity, and its causes, changed over time? Why does it persist in some areas after Uribe's demobilization process but not in others? We use multilevel modeling to explore the determinants of paramilitary human rights violations. A varied range of aspects potentially associated with the paramilitary presence at the municipal level for the period 2002-2015, such as state presence, resources, greed, grievances and conflict are analyzed. The study uses information about paramilitary human rights violations from the Centro de Investigación y Educación Popular (CINEP). Results suggest that the demobilization process reduced the initial paramilitary motivation to fight against leftist guerrilla. However, other factors such as coca cultivation or ranching remained significantly related to the paramilitary activity. The analysis at the municipal level provides clear warnings for continued violence cycles threatening any undergoing or future peace processes or demobilizations and calls for a more nuanced concept of state capacity to understand paramilitary violence.

El objetivo de este trabajo es analizar los determinantes de la productividad laboral en México a nivel estatal durante el período 2003-2016 usando datos anuales. La técnica GMM es utilizada para estimar un modelo de regresión espacial de datos panel. La especificación del modelo incluye una matriz espacial (W), el rezago espacial de la variable dependiente (ρ), el rezago espacial de los residuales (λ), y el uso de variables instrumento para reducir la endogenidad de la variable violencia. Los resultados indican que la crímenes asociados con el tráfico de drogas producen un efecto negativo en la productividad laboral. Así también, la violencia en estados contiguos produce efectos spillover en la producción por trabajador en un estado en específico. La inversion pública tiene un efecto positivo y significativo en la productividad laboral mientras que la crisis financiera durante el período 2008-2009 produce un efecto negativo.