Climate not to blame for African civil wars

Abstract

Vocal actors within policy and practice contend that environmental variability and shocks, such as drought and prolonged heat waves, drive civil wars in Africa. Recently, a widely publicized scientific article appears to substantiate this claim. This paper investigates the empirical foundation for the claimed relationship in detail. Using a host of different model specifications and alternative measures of drought, heat, and civil war, the paper concludes that climate variability is a poor predictor of armed conflict. Instead, African civil wars can be explained by generic structural and contextual conditions: prevalent ethno-political exclusion, poor national economy, and the collapse of the Cold War system.

Fig. 1.

Trends in climate and civil war in Africa (1960–2005). (Upper Left) Deviation from mean annual precipitation in the period, calculated from precipitation data from the Global Precipitation Climatology Centre (19). (Upper Right) Deviation from mean annual temperature in the period based on statistics from the Climate Research Unit, University of East Anglia (20). (Lower Left) Frequency of countries with outbreak and incidence of civil wars (at least 25 battle-related deaths per year) in Africa, as defined by the UCDP/PRIO Armed Conflict Dataset v.4–2009 (11). (Lower Right) Low and high estimates of annual war deaths in Africa derived from the PRIO Battle Deaths Dataset v.3 (14).

Fig. 2.

Ninety-five percent confidence interval bands for change in the estimated probability of civil war with a shift from the 10th to the 90th percentile value on the selected climate variable, all other parameters held at median values. Results for six alternative climate measures in five sets of regressions are shown: 1a–f represent models with civil war outbreak as the dependent variable; 2a–f represent major civil war outbreaks; 3a–f represent civil war incidence; 4a–f represent major civil war incidence; and 5a–f represent major civil war years only. Model suffix reflects climate parameter: a is absolute temperature (t−1); b is temperature growth since previous year (t−1); c is temperature anomaly (t−1); d is absolute precipitation (t−1); e is precipitation growth since previous year (t−1); and f is precipitation anomaly, i.e., deviation from normal (t−1). All models are estimated through robust logit regression with controls for ethno-political exclusion, GDP per capita, post-Cold War period, and past conflict.