**Tracking to reduce attrition** At baseline we were clear about our desire to stay in touch. We took photos and signature samples, and collected as many as ten different ways to contact each respondent. We documented contact information for each respondent, including all the places they said they sometimes stay, plus contact information for the network of people around them who have a more stable location. Respondents were often on the run from the police or other people, and so their contacts might be uncomfortable speaking to enumerators and revealing the respondent’s location. Thus, after the baseline survey, we asked respondents to use the enumerator’s phone to call their most stable contact and introduce the enumerator and study and give permission.

At each endline, enumerators would typically start with the phone numbers of the various contacts or respondent and try to arrange an appointment. Contacts received no financial incentive. Failing that they would begin visiting the various locations listed. A slight majority of respondents were found within a few hours. In other cases, all leads were cold and more extensive sleuthing and asking around the neighborhood was required. If someone had traveled or moved far away, enumerators either waited until they returned or traveled across the country to find them in person.

On the upper tail, it could take three to four days of physical searching to find the hardest-to-locate people. Enumerators only stopped searching when all possible leads had been exhausted.

**Response rates** Table A.4 lists survey response rates by treatment group and survey wave (short term, pooling 2- and 5-week surveys, and long term, pooling 11- and 13-month surveys). It also reports the p-value from a t-test of the difference between the response rate in each treatment group and the control group. None of the differences are statistically significant, and all are within about a percentage point of the control group response rate. The control group response rate is a tiny bit lower in the long run surveys and a tiny bit higher in the short run ones. But none of these differences control for covariates or even strata fixed effects, as in the next table.

**Correlates of attrition and compliance** We analyze the correlates of attrition in Columns 1 and 2 of Table A.5, which reports an OLS regression of an indicator for attrition on selected baseline covariates.<sup>3</sup> There are not significant differences in attrition by treatment group, substantively or statistically. Those who attrit are slightly wealthier and have slightly poorer mental health. In all, the treatment indicators and covariance are jointly significant at _p_ = 0.047 so attrition is not ignorable. This is one reason we control for covariates in all treatment effects regressions.

# **A.4 Treatment compliance**

Figure A.1 displays the distribution of class attendance for those assigned to therapy. NEPI did not collect attendance data during the first week (three sessions), so for simplicity we assume that all participants who attended at least one session after week one also attended the first three sessions.

We use two definitions of compliance. Our first measure is defined as “attending at least 8 days of therapy”, or about three of the eight weeks. Our second measure is defined as attending at least 80% of sessions (16 classes plus the 3 in the first week).

We analyze the correlates of compliance in Columns 3 through 8 of Table A.5. Being assigned to cash in addition to therapy did not affect the likeliness of attending therapy, which is to be expected since the cash grants were not known to participants until after therapy. The main correlates of

> 3We do so to reduce collinearity and thus ease interpretation. Results with full covariates draw similar conclusions.

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