on the extensive (by 12ppt) and on the intensive margin (by BDT 144, or 23% relative to control).<sup>22</sup> Next, I analyze the effects on ultra-poor households’ participation in food transfers. Table 4 presents the findings. On average, 94% of the control group reported that their household received food transfers. The program led to a small (1.3ppt) increase in this rate. Moreover, ultra-poor in treatment communities reported 0.10 more households as sources of food transfers, a 4% increase relative to the control group. Looking at the corresponding effect on food transfers given by ultra-poor households, columns 3 and 4 of the table show that ultra-poor were 7ppt more likely to give food transfers to others and on average they transferred food to .23 more households (18% more relative to control).<sup>23</sup> The rest of the Table shows that these changes are driven by changes in food transfers _within_ the village (Panel B), while food transfers sources from outside the village are slightly lower (Panel C).<sup>24</sup> To summarize, the findings in this section suggest that the program crowded out informal transfers received by ultra-poor households, but this effect is less pronounced for within-village transfers. If anything, it led to a modest increase in the value of transfers received and the number of food transfer sources within the community.

> 22In Appendix S2, I compare the treatment effects measured at midline and endline surveys. Table S2.1 shows that the treatment effects at midline are not statistically different from those estimated at endline. However, on the intensive margin, the large point estimates for _θ_ suggest the crowding out effect (on the intensive margin) is not diminishing, and possibly getting larger, over time. It is possible to conduct the same analysis on informal loans exchanged with other households. Appendix Table S1.8 presents the treatment effects on interhousehold loans received/given by ultra poor households. The program lowers the value of informal loans received by ultra poor households, while it increases both the likelihood of giving loans and the value of loans given by ultra poor to other households. As a result, in net, value of loans received by ultra poor household goes down, by nearly 100% relative to the control group. This is true for both loans within and outside the village. These findings complement the results reported in Bandiera et al. (2017) where I analyzed the treatment effects on likelihood of receiving and giving loans (see Table IV). I showed that the program increased the likelihood of both receiving and giving loans by the ultra-poor. The key difference between the results in Bandiera et al. (2017) and those reported here is the fact that loans received in Bandiera et al. (2017) include formal loans, whereas the results in Table S1.8 are limited to interhousehold loans alone.

> 23For food transfers, data on the intensive margin (value of transfers) was not collected. However, at midline and endline surveys, respondents were asked to report whether their households’ frequency of borrowing (lending) from (to) households reported as sources (recipients) of food transfers at baseline had increased, decreased or remained the same. In Appendix Table S1.5 I use this information to test if the program affected the frequency of borrowing or lending food to baseline network partners. Overall, I fail to find a consistent effect. Ultra-poor in treated communities were (relative to control) less likely to say their borrowing from baseline sources of food transfers had increased, but they were no more likely to say it had decreased; and there was no significant change in their frequency of giving food to baseline recipients either. Based on this, I conclude that the program did not crowd out food transfers the ultra-poor exchanged with their baseline network members. On the other hand it led to a modest increase (on the extensive margin) in food transfers the ultra-poor exchanged with other households within their communities.

> 24Table S2.2 in Appendix S2 tests whether the treatment effects at midline differ from those at endline. The effects typically get larger in magnitude by the endline, the differences are never precisely estimated.

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