We use georeferenced information on the location of violent events in sub-Saharan African countries and provide evidence that external income shocks are important determinants of the intensity and geography of civil conflicts. More precisely, we find that (a) the incidence, intensity, and onset of conflicts are generally negatively and significantly correlated with income variations at the local level; (b) this relationship is significantly weaker for the most remote locations; and (c) at the country level, these shocks have an insignificant impact on the overall probability of conflict outbreak but do affect the probability that conflicts start in the most opened regions.

Abstract This paper provides direct evidence that learning about demand is an important driver of firms’ dynamics. We present a model of Bayesian learning in which firms are uncertain about idiosyncratic demand in each market and update their beliefs as noisy information arrives. Firms update their beliefs to a given demand shock more, the younger they are. We test and empirically confirm this prediction, using the structure of the model, together with exporter-level data, to identify demand shocks and the firms’ beliefs about future demand. Consistent with theory, we also find the learning process to be weakened in more uncertain environments.

We combine georeferenced data on mining extraction of 14 minerals with information on conflict events at spatial resolution of 0.5 o × 0.5 o for all of Africa between 1997 and 2010. Exploiting exogenous variations in world prices, we find a positive impact of mining on conflict at the local level. Quantitatively, our estimates suggest that the historical rise in mineral prices (commodity super-cycle) might explain up to one-fourth of the average level of violence across African countries over the period. We then document how a fighting group's control of a mining area contributes to escalation from local to global violence. Finally, we analyze the impact of corporate practices and transparency initiatives in the mining industry. (JEL C23, D74, L70, O13, Q34)