Attanasio et al. (2022) selected a sample of 4,350 applicants in 232 different daycare-centerby-age-group drafts to measure the impacts of attending these daycare centers.<sup>8</sup> They conducted surveys in 2008 ( _N_ = 3,776), 2012 ( _N_ = 1,462),<sup>9</sup> and 2015 ( _N_ = 2,050) and studied the effects on children’s cognitive function, anthropometrics, and behavior; on labor market outcomes of household members; and on the economic standing of the household (e.g., income and assets). See Attanasio et al. (2022) for further details about how the sample of 4,350 children was selected.

To study the effects of daycare attendance on economic preferences and on decision-making abilities, we surveyed 2,113 of the children from the sample in late 2016, early 2017 – 9 years after those selected in the lottery started attending daycare. Most of the children were at this time between 9 and 13 years old. While large, the rates of attrition are comparable to other long-run longitudinal surveys in poor countries.<sup>10</sup> The attrition rates among the control children are 3-4 percentage points larger than the rates among treatment children (see Appendix Table 1). Appendix Table 2 shows however that, at least _in terms of observables_ , there is no differential selective attrition between the treatment and control children.

It is worth noting the unusually challenging circumstances under which the study was conducted. Most participants lived in _favelas_ in areas that were not infrequently of restricted access because they were controlled by drug-trafficking gangs or by militias. Families often lived in crowded spaces with multiple family members sharing one or two bedrooms. Tracking study participants was not any easier given that dwellings in these areas typically have no official addresses.

We start by documenting that pre-treatment variables are balanced for the sample of children analyzed in this paper. The first column of Table 1 shows means for “control children”, i.e., the children with higher lottery numbers who were put on the waiting list. The second column shows differences in means between the control and the “treatment children” (i.e., the children with the

> 8 We only use information from the original waiting list, before applicants had the opportunity to accept or reject their placements (as opposed to using lottery status after some original winners already refused the offered slot, which was then offered to the first available person in the waiting list), thereby avoiding concerns about randomized list designs raised in Chaisemartin and Behagel (2020).

> 9 Because of budget constraints, the 2012 survey targeted only 60% of the original sample.

> 10 The original sample drawn based on the information from the applications consisted of 4,350 children, which would imply an attrition rate of 51.8%. The first survey, which was conducted in 2008, managed to survey just 3,776 of these children. That is, almost 15% of the original sample was lost in 6 months (the time between when applications were submitted and when the 2008 survey was conducted). Such attrition occurred mostly because the application data did not have accurate contact information on the applicant-families. Relative to the 2008 survey, the attrition rate was of 44%.

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