Date of Award
6-1-2013
Document Type
Masters Thesis
Degree Name
M.A.
Organizational Unit
Josef Korbel School of International Studies
First Advisor
Erica Chenoweth, Ph.D.
Second Advisor
Ved Nanda
Third Advisor
Barry Hughes
Fourth Advisor
Lindsay Heger
Fifth Advisor
Lewis Griffith
Keywords
Extrapolation model, Insurgency, Power law, Red Queen hypothesis, Terrorism
Abstract
Recent empirical studies suggest insurgencies may be accurately described by aggregated extrapolation models, such that past behavior becomes the best predictor for future action. I argue that aggregated extrapolation models possess two flaws that make it a poor choice for examining insurgencies. First, aggregated extrapolation models ask the wrong question. The more interesting question is to ask when present action is no longer explainable by past behavior. Secondly, aggregate models mask changes that a phenomenon undergoes over time which are only revealed upon disaggregating the data. Starting with a model and findings provided by Neil Johnson, I use casualty data from the Iraq War to offer an alternative method to identify changes in the phenomenon under observation with the addition of no new data. Presenting an alternate set of findings, I propose it is possible to identify ‘game changer’ events with the introduction of breakpoints to observe for distinct departures from the baseline trajectory
Publication Statement
Copyright is held by the author. User is responsible for all copyright compliance.
Rights Holder
Micah Dolcort-Silver
Provenance
Received from ProQuest
File Format
application/pdf
Language
en
File Size
110 p.
Recommended Citation
Dolcort-Silver, Micah, "Recognizing 'Game Changers' in Extrapolation Models: An Application to Counterinsurgency" (2013). Electronic Theses and Dissertations. 166.
https://digitalcommons.du.edu/etd/166
Copyright date
2013
Discipline
International relations