This absence of a conflict effect in the household data can be accounted for by three factors. First, it may be related to the sample time span (2012–2013), as for this earlier period the surge in international jihadism in the region had only started to materialize, and hence the mechanisms linked to sabotage and rent-seeking were less salient.<sup>25</sup> Second, the findings from the household data (based on domestic respondents only) are consistent with the notion that the likelihood of within-village conflict has barely changed, and the lion’s share of the overall conflict surge can be attributed to international jihadist groups.<sup>26</sup> Finally, the smaller sample size of the household data may matter as well. In particular, note that a traditional, ”small-scale” RCT based on 150 clusters of villages may not be powered to detect impacts on the incidence of (rare) conflict events. Our main results at the village level rely on a much larger set of observations (nearly 4,000 villages).<sup>27</sup> Another key distinction is that the household data is bound to rely on self-reported conflict information, while the village-level data draws on reports and articles from a broad set of media and NGO sources.

Taken together, the household-level results show no evidence of a decrease or increase in conflict between community members, while the village-level results highlight an increase in events perpetrated by foreign terrorist actors. This suggests that the cash transfer program affected conflict mostly by shifting the incentives of actors outside the village rather than by altering opportunity costs to engage in conflict for local populations.

# **4 Discussion and Conclusion**

This paper has presented novel, large-scale evidence of the impact of a government-led unconditional cash transfer program on the likelihood of conflict in Niger. Causal identification relies on the randomization of the program through public lotteries within communes. The results show that, during treatment, there was a temporary increase in conflict events, which was mainly driven by attacks by foreign terrorist groups. These findings are consistent with the terrorists’ attempts to sabotage successful government policies as well as incentives to appropriate rents. The fact that this increase in conflict proved temporary could be consistent with a reduced incidence of sabotage and rent-grabbing after the end of the program, when the government was less present and financial flows had ceased. In addition, medium-run productivity increases may have raised the opportunity costs for locals to engage in conflict.

In terms of magnitude, severe conflict events remain quite rare, and we find that cash transfers increase their likelihood by 0.6 to 1.7 percentage points. Hence the welfare costs of these conflict events would need to be between 59 (1/0.017) to 166 (1/0.006) times larger than the welfare benefits of cash transfers for the two effects to fully cancel out. Cash transfers have indeed been shown to have robust welfare effects in the international literature. In Niger, cash transfers were found to increase consumption by 10 percent on average (Premand and Barry 2022; Premand and Stoeffler 2022), and led to lasting effects on asset accumulation (Stoeffler et al. 2020) and income-generating activities when complemented with productive

> 25In fact, if we restrict the village-level data to the waves for which microdata are available, we do not find an increase in conflict events either (see Table A8, cols. 1–2).

> 26This evidence is consistent with other research on the Niger cash transfer program that shows positive effects of complementary livelihood interventions on social well-being and social cohesion, with no evidence of increased community tension (Bossuroy et al. 2022). Premand and Schnitzer (2021) also analyze the application of household targeting methods and find no effect on the selfreported likelihood of conflict, which—if anything—seems to decrease in the villages over time between the start and the middle of the program.

> 27As such, the paper illustrates that very large samples are required to analyze the impacts of policy interventions on rare outcomes such as conflict events. The sample size of typical RCTs for which micro-data is collected would not be sufficient in our setting. On a related note, the unavailability of micro-data across a very large number of villages also limits our ability to analyze a wide range of intermediary outcomes to tease out mechanisms.

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