Abstract

Military coups are the most consequential breakdown of civil-military relations. This dissertation contributes to the explanation and prediction of coups through three independent quantitative analyses. First, I argue that food insecurity is an important determinant of coups. The presence of hunger can generate discontent in society and subsequently alter coup plotter opportunities. Furthermore, I show that the presence of chronic hunger can condition the effect of increasing development. While increasing levels of development have been shown to limit coup proclivity, a state experiencing chronic hunger will recognize the fundamental failure of basic needs provision. As development increases, the presence of chronic hunger in a state will therefore increase the likelihood of a coup when compared to its absence. Findings indicate that food insecurity, and specifically the conditioning influence of chronic hunger, are important explanatory predictors of coups. In the second analysis, I argue that existing tests of the Coup-Contagion hypothesis have not been sensitive to the specific pathways through which coups may diffuse. After a robust analysis of spatial autocorrelation, I derive a novel feature of contagion that is sensitive to both shocks and historical legacy of neighborhood coups. Regression models including coup contagion as a predictor, provide substantive support for my hypotheses. In the final assessment, I synthesize explanatory models and provide a machine learning framework to forecast coups. This framework builds on a growing effort in social science to predict episodes of political instability. I leverage a rolling origin technique for cross-validation, sequential feature selection, and an ensemble voting classifier to provide forecasts for coups at the yearly level. I find that predictive sensitivity to coups is increasing over time using these methods and can result in practical forecasts for policy makers.

Notes

If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu.

Graduation Date

2020

Semester

Summer

Advisor

Powell, Jonathan

Degree

Doctor of Philosophy (Ph.D.)

College

College of Sciences

Department

School of Politics, Security, and International Affairs

Degree Program

Security Studies

Format

application/pdf

Identifier

CFE0008192

Language

English

Release Date

August 2020

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

Share

COinS