Historical evidence suggests that once insurgencies become well-established, resolving them can take several years, is often quite bloody, and may not be definitive (many insurgencies recur). In many cases, the cost of conducting a prolonged counter-insurgency campaign is very costly for governments while producing only marginal success. On the other hand, while we often focus on long and bloody insurgencies, history also demonstrates that most nascent insurgencies actually fail quickly. This project develops a series of agent-based computer simulation models to aid in understand some of the complexities associated with defeating insurgencies and determining which are likely to drag on, and which will be defeated quickly. In particular, these models will help us address three questions. First, what leads some insurgencies to become well established and resistant to collapse, while others fail quickly? Second, when do insurgencies reach the point where they are likely to survive, despite government repression? Finally, how can governments effectively adapt their counter-insurgency strategies to stem the growth of insurgency?

The simulation models the early stages of insurgency where the interactions of civilians, insurgents, and soldiers (government forces) are critical. At early stages of insurgency, civilians constitute an audience for insurgent-soldier interactions, and can join the insurgency or be deterred from joining it. Actions by insurgents who can attack government targets, and in turn be attacked and captured or killed, set the stage for civilians to change loyalties. Initial simulations have revealed the critical importance of accuracy on the part of governments/soldiers who seek to capture insurgents, since government military actions against insurgents sometimes backfire. A series of extensions to the initial simulation model are developed, focusing on insurgent and government recruitment, learning, and the interactions of multiple insurgent groups.

The development of the simulation models is coupled with statistical analysis to determine whether the patterns observed in the simulations are also present in international politics. The project examines a population of insurgencies and sees whether factors that the model suggests will predict patterns of insurgencies in fact do so. In particular, insurgency duration, the speed at which insurgency grows, and the scope of penetration of the insurgency into the local population are examined. Along with construction of various proxy measures of the models? concepts, the project incorporates the collection of new data about insurgencies and counter-insurgency efforts to be able to better test the hypotheses that emerge from the simulations.

The broader impacts of the proposal include the revelation of important patterns of duration and termination of insurgency, both from the simulation and empirical analysis, and confirming the presence of these patterns and relationships between variables in the international system. In particular, understanding the circumstances under which different types of government actions may be useful or counterproductive may offer specific policy advice, with empirical backing. Understanding these patterns and relationships may help in the design of appropriate strategies for confronting existing insurgencies and avoiding their emergence in the first place.

Project Report

This project aimed to develop a series of computational, agent based models to examine the growth of insurgency from infant rebellions, to terrorist groups, to large scale insurgencies that hold territory. These simulations would then be tested with statistical analyses using new data on terrorist campaigns in African states. In addition to identifying what local factors contribute to the growth of violent political movements, the project also examines how foreign states and macroeconomic policies may contribute to the growth of violent non-state actors. One of the major findings of the project is how foreign entrance into terrorist campaigns may create a series of perverse incentives. We find that while political violence is typically motivated by local issues, the effects of terrorism at the local level may create negative economic externalities for other states in the system. For example, terrorism in Nigeria creates spikes in the cost of doing business for multinational firms in the Niger Delta, which may translate into increases in the price of oil. Therefore, foreign states may have incentives to aid governments that are fighting terrorist movements. Our theoretical results, however, demonstrate that this may accelerate the conflict for two reasons. First, foreign support for governments may increase their effectiveness in harming large parts of their population, but not necessarily their accuracy. This means that more civilians may turn to the insurgency. Second, since the government may benefit from the flow of resources from foreign states, but can only obtain these benefits if the insurgency remains active, governments may have incentives to protect terrorist organizations from collapsing. These hypotheses are empirically supported in Bapat (2011). Policywise, these results have several implications for the ongoing 'war on terror.' First, we should expect leaders in vulnerable political positions to make considerable efforts to link insurgencies in their territory with al Qaeda or the larger war on terror. Second, we should expect that efforts to support governments against their militant challengers will likely increase terrorist violence in the short run, but decrease the possibility that insurgencies will succeed. In the long term, it is likely that a population wll turn away from terrorists.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Type
Standard Grant (Standard)
Application #
1000344
Program Officer
Brian Humes
Project Start
Project End
Budget Start
2010-09-01
Budget End
2013-08-31
Support Year
Fiscal Year
2010
Total Cost
$185,990
Indirect Cost
Name
Pennsylvania State University
Department
Type
DUNS #
City
University Park
State
PA
Country
United States
Zip Code
16802