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Predicting the Intensity and Location of Violence in War

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Predicting the Intensity and Location of Violence in War THE FLORIDA STATE UNIVERSITY COLLEGE OF SOCIAL SCIENCES AND PUBLIC POLICY PREDICTING THE INTENSITY AND LOCATION OF VIOLENCE IN WAR By ANDREAS BEGER A Dissertation submitted to the Department of Political Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy Degree Awarded: Summer Semester, 2012 Andreas Beger defended this dissertation on May 29th, 2012. The members of the supervisory committee were: Will H. Moore Professor Directing Dissertation Victor Mesev University Representative Jason Barabas Committee Member Megan Shannon Committee Member Mark Souva Committee Member The Graduate School has verified and approved the above-named committee members, and certifies that the dissertation has been approved in accordance with the university requirements. ii To my family, Vesna and Alexander, who kept me alive in 2010 and 2011. iii ACKNOWLEDGMENTS I would like to thank my committee, Will H. Moore, Mark Souva, Jason Barabas, Megan Shannon, and Victor Mesev, for their advice and feedback throughout this process. After my time in Iraq in 2009 and while in Washington, D.C. in 2010, Will Moore encouraged and prodded me to “get back in the saddle”. I am very grateful for that. Dale Smith, Charles Barrilleaux, Cherie Maestas, and Jerry Fisher in the Department of Political Science have been very flexible and generous in their support. I have spent considerable time away due to outside obligations while studying here, and the Depart- ment has been consistently accommodating and understanding. Sally Anderson, Courtenay Conrad, Jacqueline DeMeritt, Matt Golder, Daniel Hill, Daniel Milton, Chungshik Moon, Marius Radean, Meredith Whiteman and Joseph Young have been incredibly helpful with their feedback over the years. One of the projects in this dissertation began in Paul Hensel’s international conflict class. iv TABLE OF CONTENTS List of Tables.......................................... vii List of Figures......................................... viii Abstract............................................ xii 1 Introduction1 2 Predicting the level of fatalities in interstate wars3 2.1 Introduction.....................................3 2.2 How long will states bear the costs of war?...................5 2.2.1 Incomplete Information..........................5 2.2.2 Commitment Problems..........................6 2.2.3 Military decision..............................7 2.3 Data and methods.................................8 2.3.1 Estimation strategy.............................9 2.3.2 Explanatory variables........................... 10 2.4 Empirical results.................................. 12 2.4.1 Regarding the hypotheses......................... 12 2.4.2 Robustness checks............................. 13 2.4.3 Regarding overall model fit........................ 14 2.4.4 Out of sample predictions......................... 15 2.5 Discussion and conclusion............................ 16 3 Using front lines to predict deaths in the Bosnian war 26 3.1 Introduction..................................... 26 3.2 Disaggregated studies of civil conflict...................... 28 3.3 Ethnic violence and point data on deaths.................... 29 3.3.1 How the data are used........................... 29 3.3.2 The special case of Bosnia......................... 31 3.3.3 Yugoslav identity.............................. 32 3.3.4 Frontlines.................................. 33 3.4 Data and model................................... 35 3.4.1 Model setup................................. 35 3.4.2 Model specifications and variables.................... 37 3.4.3 Estimation.................................. 38 v 3.5 Results........................................ 39 3.5.1 Parameter estimates............................ 39 3.5.2 Model fit................................... 40 3.6 Conclusion...................................... 42 4 Modeling the evolution of civilian deaths in the Iraq War 58 4.1 Introduction..................................... 58 4.2 Background on Iraq and IR forecasting..................... 60 4.2.1 Counterinsurgency and violence against civilians........... 60 4.2.2 Research on the Iraq War......................... 61 4.2.3 Forecasting in International Relations.................. 62 4.2.4 Why we need well-fitting models for policy............... 63 4.3 Violence against civilians in Iraq......................... 65 4.3.1 Data and machine-coding......................... 65 4.3.2 The dynamics of violence during the Iraq War............. 67 4.4 Modeling civilian deaths.............................. 68 4.4.1 LN-EWMA: modeling effects....................... 69 4.4.2 LN-logistic: From peak oil to peak conflict............... 71 4.4.3 Model fit................................... 73 4.4.4 Peak violence and the troop surge.................... 74 4.5 Conclusion...................................... 75 5 Conclusion 87 Appendices .......................................... 89 A Replication code for Bosnia chapter 89 A.1 JAGS code: Constant-only negative binomial model............. 89 A.2 JAGS code: Constant-only spatial count model................ 89 B Replication code for Iraq chapter 91 B.1 Coding incident location.............................. 91 B.2 JAGS code: LN-EWMA............................... 93 B.3 JAGS code: LN-logistic............................... 94 References ........................................... 95 Biographical Sketch..................................... 106 vi LIST OF TABLES 2.1 Variable descriptions and sources......................... 21 2.2 Log-normal regression of war duration...................... 22 2.3 Truncated normal regression of war fatalities.................. 23 2.4 Variable significance................................. 24 2.5 Model predictions for selected wars........................ 25 3.1 Comparison of model fit............................... 43 4.1 Civilian deaths from March 2003 to February 2012 by province........ 79 vii LIST OF FIGURES 2.1 Predicted and observed war deaths for the best-fitting model. The x-axis lists the wars in the sample, with the observed number of war deaths indi- cated by the red dot. The list is ordered by the total number of deaths, rang- ing from the Falklands war to the eastern front of World War 2. The number of war deaths is on a logarithmic scale. The blue bars show the interval con- taining 95% of the predicted war deaths in each bootstrap iteration. The intervals correctly bracket observed deaths for 69% of all wars......... 19 2.2 Predicted and observed war deaths for selected wars. The predictions for the Eritrean-Ethiopian and Kargil wars are out of sample forecasts. Bars show low and high estimates for observed fatalities and 95% range for model predictions. Points show best or median estimate for observed and pre- dicted fatalities respectively. The scale is logarithmic with base 10, so for example 103 1,000 deaths............................. 20 Æ 3.1 Illustration of conflict incident point data and aggregation to grid cells or administrative units.................................. 43 3.2 Comparison of Armed Conflict Location and Events Dataset (ACLED) and Research and Documentation Center (RDC) incident data for the Bosnian War............................................ 44 3.3 Proportion of people who self-identified as being Yugoslav, rather than Serb, Muslim, Croat, etc. during the 1991 census. The rates are higher in cities, especially Tuzla and Sarajevo, where 15 to 20 percent of all respondents la- belled themselves as Yugoslav, and lower in eastern Bosnia, Herzegovina in the south, and parts of western Bosnia adjacent to Dalmatia.......... 45 3.4 Ethnic diversity by municipality. Based on 1991 census............. 46 viii 3.5 Bubbleplot of Yugoslav self-identification, ethnic diversity, and civil war death rates by municipality. Each circle represents a municipality, with its propor- tion of self-identified Yugoslavs on the x-axis and ethnolinguistic fractional- ization index (ELF) value on the y-axis. The area of the circle is proportional to deaths per capita during the civil war. There are fewer Yugoslavs in eth- nically less diverse municipalities, as one would expect, and those also tend to see relatively little violence. In municipalities with a high level of diver- sity, the proportion of Yugoslavs is related to deaths per capita, with diverse but nationalist municipalities experiencing more violence than diverse but federalist municipalities............................... 47 3.6 Deaths per 1,000 by municipality during the Bosnian War, 1992-1995. The rate of deaths is highest in eastern Bosnia in the municipalities that con- tained Bosniak enclaves during the war, and in areas of western Bosnia that were ethnically cleansed early in the war. From the IDC Bosnian Atlas of War Crimes....................................... 48 3.7 Histograms of deaths by municipality during the Bosnian War, 1992-1995. The untransformed count of deaths fits a negative binomial distribution with mean 712 and dispersion parameter 0.99. Both the log of deaths and population-adjusted deaths are skewed...................... 49 3.8 Approximate 1993 front lines. Digitized using information on land mines from BiH Mine Action Center (posted at www.mine.ba)............. 50 3.9 Predicted versus observed killings during the Bosnian War. Each panel shows a plot of predicted counts compared to observed counts for the base, ethnic, frontline, and combined models respectively. The axes are on a log10 scale. The black line shows observed = predicted. Each plot also gives the deviance information
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