GOVERNANCE AND SOCIAL PROTEST IN THE WAKE OF NATURAL DISASTERS. A Spatial Analysis of Social Protests in Central America and the Caribbean
Numerous conflict-studies have explored the link between natural disasters and conflict and have revealed mixed results. In view of this ambiguity, it seems evident that conditions such as the characteristics of the state matter for the occurrence of conflicts in the aftermath of natural disasters. The institutional quality of the state, for instance, is regarded as one of the core moderators of natural disaster induced conflicts. However, the concept of Quality of Government (QoG) remains largely understudied. Based on a new theoretical framework, this thesis proposes that regions with low QoG are more likely to experience social conflicts in the aftermath of natural disasters. The focus will be on social protests that evolve spontaneously and die down quickly as the circumstances of natural disasters mostly do not allow for large-scale mobilization. In that respect, my study differs from existing studies on natural disasters and intrastate or non-state conflicts. By conducting a spatial analysis, I test whether QoG moderates the effect between natural disasters and social protests in seven Central American and three Caribbean countries during the period 2008-2015. For that purpose, I created a new geographically disaggregated data set at the municipality level that allows exploiting the within-variation of the countries. The data set combines various high-frequency geo-referenced data sets on natural hazards with spatial data on social protests from the Social Conflict Analysis Database (SCAD) and with municipality based public opinion data from the AmericasBarometer. The results provide support for the theory that areas with low QoG are associated with more social protests in the wake of natural disasters. Moreover, I find that this is particularly pronounced with respect to the bureaucratic quality of the state. My core findings remain robust across all model specifications and robustness checks.