support cut-off). The endline sample size was determined based on power calculation to detect minimum effects between 0.15 standard deviations (for the pooled treatment) and 0.23 standard deviations (for comparisons across arms), for a power level of 80% and significance level of 5% and using baseline data for the intra-cluster correlation (ICC) parameter. Note that spillover effects are likely smaller than direct treatment effects, hence the design is not powered to detect very small spillovers, and we focus on analyzing spillovers for the pooled treatment.<sup>28</sup> The main sample includes 2,936 “selected” individuals (above the common vulnerability cut-off in treated and control localities) and is used to estimate direct impacts on economic and social outcomes.<sup>29</sup> The spillover sample includes 1,201 “non-selected” individuals (below the common vulnerability cut-off in treated and control localities) and is used to estimate local spillovers.<sup>30</sup> Control group individuals were sampled using the same vulnerability cut-off. The follow-up attrition rate was 10.6%, respectively 7.8% (using the common support cut-off), and was balanced between treatment and control groups.<sup>31</sup> Table A2 contains the detailed composition of baseline and endline samples.

The follow-up questionnaire collects data about household characteristics, employment, assets, food security, well-being, saving and debt, social relationships, community activities and interpersonal trust. A shorter version of the questionnaire was administered to the “non-selected” sample. Appendix A3 provides additional information on the main

> 28The endline survey sample was established based on power calculations to detect impacts between treatment arms and the control group. 15 “selected” individuals (respectively 17 and 22) were sampled out of localities in T1 (respectively T2 and T3). Finally, 10 “non-selected” individuals were sampled in each (rural) locality to study spillovers. When it comes to estimating spillovers, the sample size for the non-selected was determined to detect minimum effects between 0.18 standard deviations (for the pooled treatment) and 0.26 standard deviations (for comparisons across arms), for a power level of 80% and significance level of 5% and using baseline data for the intra-cluster correlation (ICC) parameter. Power was recalculated ex-post using the follow-up control group data to compute the mean, standard deviation and intra-cluster correlations for key outcomes. The minimum detectable effects remain between 0.15 and 0.22 standard deviations for the main outcomes. This means that the study is powered to detect a 20% impact (+5,300 CFA) on profits in independent activities, a 37% impact (+5,800 CFA) on starting capital or a 23% impact (+5,800 CFA) on the value of assets in the main activity.

> 29The sample includes 3,237 “selected” individuals, and the pooled specification with a common support cut-off contains 2,936 observations.

> 30The spillover sample includes 1,983 “non-selected” individuals, and the pooled specification with a common support cut-off contains 1,201 observations.

> 31In the sample of “selected” individuals, attrition is 10.56%, 11.30% and 10.44% for T1, T2 respectively T3 (using the common support cut-off). In the sample of “non-selected” individuals, attrition is 7.92%, 8.22% and 8.17% across T1, T2 respectively T3 (using the common support cut-off). In the total sample of selected individuals (not using the common support cut-off), attrition is on average 10.8% for “selected individuals” and 8.4% for “non-selected individuals”.

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