What Explains C ivil War D uration?

1. What Explains Civil War Duration? Katharina Nachbar kn1296a@american.edu American University School of International Service

2. Research Question & Research Hypotheses • Research Question Why do some civil wars last so much longer than others? Which factors determine civil war duration? • Research Hypotheses* [H1]: Ethnic conflicts last longer than non-ethnic civil wars. [H2]: Conflicts in which rebels have access to contraband financing last longer than those without such financing opportunities. [H3]: Civil wars in poorer countries last longer. * Controlling for: population size and world regions (Sub-Saharan Africa, Asia, Eastern Europe, Latin America)

3. Background Info Civil War: not a straightforward concept (unlike conventional wars, start and end dates are not easily determined) Global Trends in State-BasedConflictsby Type, 1946-2009 • Definition used: • Fightingbetween State andorganized non-stateactor(s) • At least 1,000 battle-relateddeathsovercourseof war • At least 100 deaths on bothsides Source: UCDP/PRIO, courtesyofHuman Security Report

4. Literature Review • Collier and Hoeffler (2001) • Income inequality (measured by Ginicoeff.) has most significant effect on civil war duration • GDP/capita: negatively associated with civil war duration • ‘Moderate’ level of ethnic fractionalization associated with maximum conflict duration • Population size: positively associated with civil war duration • Fearon and Laitin (2003) • RQ: What explains civil war onset? • Ethnicity or religious diversity do not explain likelihood of civil war onset • Main factor driving a country’s proneness to civil war is the feasibility of insurgency  Problem: Different studies have yielded ambiguous results!

5. Data Description Unit of Analysis: 128 civil wars occurring between 1945 and 1999 Data Source: Replication data from: Fearon, James D. “Why Do Some Civil Wars Last So Much Longer Than Others?” Journal of Peace Research 41, no. 3 (2004): 275-301. Limitations of the Data: • Only conflicts that killed at least 1,000 people (debatable approach) • Several civil wars occurred after 1999 (high number of missing cases) • Conflicts between non-state actors only not included in the dataset Dependent Variable: • Y: Civil war duration (durest) • Unit of measurement: years of conflict; LOM: interval-ratio Independent Variable: • X1: ethnic vs. mixed vs. non-ethnic conflicts (ethwar); LOM: ordinal (0 = non-ethnic war, 1 = mixed/ambiguous, 2 = ethnic war) • X2: evidence vs. no evidence of contraband financing of rebels (drugs); LOM: nominal (binary variable: 1 = ‘drugs’, 0 = ‘no drugs’) • X3: GDP/Capita; LOM: interval-ratio

6. DescriptiveStatistics Positively Skewed Distribution VS Bi-Modal Distribution (extreme scores)

7. Descriptive Statistics: Interpretation Measures of Central Tendency: • Average civil war duration: 8.76 years // Median duration: 5.50 years • Average GDP/Capita: $1799 // Median: $1360 // Range: $49 – 8314 • Ethnic wars: Mode = ethnic wars (55.12% of observations) • Contraband financing: Mode = no evidence (86.72% of observations) Interpretation: • Mean as the central tendency might be misleading due to great variance of datapoints (most cases have a duration of less than 10 years; range of data points: 1 to 52 years) • Histogram shows are relatively large dispersionwith many short civil wars and a few ones lasting several decades • The dataset only includes cases for the period between 1945-1999; data points for the period after 1999 are missing from the dataset Positively Skewed Distribution

8. Bivariate Analysis: Interval-Ratio Variables (1/2) In both cases: no clear linear relationship to be detected; clustering of data points hints to curvilinear relationships between durest and pop & gdpen; log transformation of pop does not seem to fundamentally change overall pattern

9. Bivariate Analysis: Categorical Variables (1/2) Kaplan-Meier-Curves: What is the likelihood of civil war “survival“ Largely parallel trends Non-parallel trends

10. Bivariate Analysis (2/2): Interpretation Bivariate analyses using the logrank test for survival analysis and t-test / ANOVA indicate yield the following results: • ethwar seems not statistically significantly associated with civil war duration; in other words: ethnic wars are not significantly different from mixed or non-ethnic civil wars when it comes to average conflict duration • drugs is significantly associated with civil war duration: both the logrank test (Chi2) as well as the t-test show as statistically significant relationship The Kaplan-Meier-Curves reflect those results: • ethnic wars do not seem to have a higher likelihood of ‘survival’ than mixed or non-ethnic wars (largely parallel trends) • civil wars in which rebels have access to illicit financing opportunities have a higher likelihood of ‘survival’ than those where such factors are not present at all points in time

11. The Model: Weibull Regression (Survival Analysis) • Survival analysis: typically used for ‘time to event’ data • Widely used in public health and medical research • Weibull model: proportional hazards (PH) model • Social sciences: increasingly used for duration analysis Research Context: • Time to ‘failure’ of civil war (i.e. ending of war) • Duration estimates: What is the likelihood or ‘hazard’ of war to ‘fail’ within a time period?

12. Results: Weibull Regression AnalysisThe Dependent Variable is durest (est. civil war duration) • Interpretations: • Ethnic wars are negatively associated with the likelihood of a civil war ending (b<1); in other words: ethnic wars last longer than those without an ethnic dimension • Civil wars in which insurgents have access to financing from illicit trade with diamonds, drugs etc. tend to last twice as long than those during which such opportunities are not given • Civil wars in Eastern Europe are positively associated with shorter civil war duration; i.e. they are more than 3 times more likely to end sooner than wars in other world regions • Civil wars in Asia seem to last about 5 less likely to end at any point in time than wars in other world regions p-values in brackets; coefficients report the hazard ratios indicating the probability of ‘failure’ (i.e. end) of civil war when the factor is present; they are the multiple by which an end of war becomes more likely with a one-unit change in the independent variable.

13. Findings & Policy Implications • Wars during which rebels are able to finance themselves through illicit trade channels tend to last longer (EXPL.: rebels are able to sustain themselves longer; money can be used to buy small arms & light weapons) • Regional differences: • Shorter wars in Eastern Europe (EXPL.: mostly high-intensity, high-technology  earlier stalemate) • Longer wars in Asia (EXPL.: most extreme scores among Asian countries; e.g. Burma with 52 years) • All models indicate significance for ethnic wars (EXPL.: less likely to end in negotiated settlements because they are identity-based and often perceived as zero-sum games) ++ BUT: Why does bivariate analysis suggest non-association for ethwar and durest? ++ Policy Implications: • Intl. intervention should include ‘drying up’ illicit trade channels for contraband • Fostering associational ties between ethnicities in fragile states is key to prevent long-lasting civil wars Further Research: more extensive data needed; test for greater number and variety explanatory factors; study gives only a snapshot