Master's Oral Thesis Defense: "Identifying armed group presence using Hidden Markov Models”

Speaker: Mauricio Vela Baron, Washington University in Saint Louis

Abstract: Identifying armed group presence is important to examine patterns of conflict. Armed group presence is often used as the main variable of interest in several studies, and in some cases, this variable is ignored. Many of these studies use expert data or proxy variables to analyze armed group presence. This paper proposes Hidden Markov Models (HMMs) as a method to identify armed group presence. HMMs permit identifying armed group presence at a sub-national level and in long panel data sets. A HMM is used in this paper to identify paramilitary and FARC presence in Colombia. The armed groups’ presence predictions are used to analyze the effect of economic shocks on violence.

Host: Nan Lin