interacted with other contextual variables”. However, the macro studies have rarely tested systematically for these conditioning factors, and no consensus has emerged on their importance.

On the one hand, some empirical evidence points to the fundamental importance of the underlying countries’ conditions to explain the impact of income shocks on conflict and stability. Besley and Persson (2008) show that the impact of commodity prices on conflict apply only to countries with weak constraints on executive power. When checks and balances are strong, governments are probably more constrained in the way windfall revenues from commodities’ price swings can be spent. This could in turn reduce the potential value of the ‘state prize’ to be appropriated through fighting.<sup>7</sup> However, this result may just reflect other structural differences between countries with strong constraints, mostly high-income Western democracies, and countries with weak constraints, mostly developing countries. Other studies provide evidence that the role of ethnic divisions is important in understanding the impact of income shocks on civil conflict (Hull and Imai, 2013) and political risk (Bruckner and Gradstein, 2012).<sup>8</sup> On the other hand, B-B also find that commodity price changes have no significant impact on conflict when considering only high-risk countries, defined by the type of political system, the level of economic inequality, and the degree of ethnic polarization.<sup>9</sup> Similarly, Miguel et al. (2004) do not find any difference in the impact of weather shocks on civil war between countries differing in terms of democratic rule, ethno-linguistic fractionalization, type of terrain, income per capita, or oil-exporting status. These studies thus conclude that commodity price changes have no significant impact on conflict, even in high-risk countries.

One reason for these different results is that the studies differ in significant details. The analysis in Miguel et al. (2004) is not strictly comparable with the others, as they restrict the sample to Sub-Saharan African countries. Importantly, Besley and Persson (2008) and Hull and Imai (2013) use a different way of coding civil wars than B-B (explained below), and Bruckner and Gradstein (2012) examine the impact on political stability rather than on conflict per se. In addition, B-B use various conflict data sets and find a significant effect of the conditioning factors in some specifications, although it is not clear in which ones as they do not report the individual interaction terms.

Equally importantly, many of the conditioning factors tested by the studies are not necessarily the most important to spurring a conflict in the presence of adverse trade shocks. For example, it is not clear whether the distinction between democracies and nondemocracies should matter in a country’s response to external shocks. Miguel et al.

> 7 This argument appears to have less power in the case of rebel. If the rebels can physically take control over resources, then whatever legal arrangements are in place to limit authority for spending the funds would not be relevant.

> 8 The former study captures ethnic divisions via the ethno-linguistic fractionalization index, while the latter focuses on ethnic polarization from Montalvo and Reynal-Querol (2005).

> 9 In particular, these sub-sets of countries include non democracies, autocracies, regimes with low executive constraints, low-income countries, highly unequal countries, countries with high ethnic polarization and countries in Sub-Saharan Africa.

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