based sessions, 0 otherwise. i denotes a set of baseline characteristics of student _i_ in school _j_ . In the baseline specification, i includes a dummy for whether the student is attending the evening XX shift, gender, the lower secondary school GPA, whether they had taken part in the COMIPEMS assignment twice, the math and Spanish average. Since the randomization has been conducted XX within school, and the number of students potentially eligible defined in accordance with the number of available tutors, all the regressions account for school fixed effects ( ). In eq. (1) 1 and 2 are the parameters of interest, since they capture the effect of being assigned either to ii the 10 sessions or the 20 sessions group. μμ ββ ββ As discussed in section 2.3, attendance to the CBT-based sessions was very low. The limited compliance makes the ITT effects not particularly informative, therefore we complement it with the Average Treatment Effects (ATE). Among students assigned to the two treatment groups, the decision to attend a certain number of sessions might be related to student observable and unobservable characteristics. In order to account for selection, we use two alternative strategies. In the first one, we assume that students’ decision about the number of sessions to attend only depends on their observable characteristics. Therefore, under the assumption that the selection is based on observable characteristics, we use matching methods to estimate the following multivalued treatment effect equation below: valued treatment effect equation below: i 0(0S S )i 1(1t 4S S )i 2(5p S i i 0S S i takes the value 1 if student (2) YY = αα+ ππ _i_ , who was originally assigned to any of the treatment groups, + ππ +ππ uuS SS) + uu took 0 sessions, 0 otherwise; 1to4S S i takes the value 1 if student _i_ , who was originally assigned to any of the treatment groups, took between 1 and 4 sessions, 0 otherwise; 5p S i takes the value 1 if student _i_ , who was originally assigned to any of the treatment groups, took 5 sessions or more, 0 otherwise. The omitted category in eq. 2 is represented by individuals in the control group. uuS SS The parameters 0, 1 and 2 measure the ATE of taking 0, 1 to 4 sessions and more than 5 sessions. When looking at the effects of CBT sessions, we focus on categorical variables, since for policy purposes it is more interesting to identify whether there is a threshold effect rather than the ππ ππ ππ effect of an additional session. To increase the probability of matching student _i_ with a student who is observationally equivalent, we do not control for school fixed effects, thus allowing for potential pairs to be assigned in different schools.

# **4.2 Baseline Data**

The main sources of data at baseline are the administrative records from the COMIPEMS assignment process, which allows us to observe the full ranked list of schooling options requested; the score in the admission exam (measuring math and Spanish language); the GPA in lower secondary; plus the information contained in the socio-demographic survey filled out at registration, which provides us with variables such as gender, age, parental education and occupation, assets, and more.

Table 2 presents the baseline characteristics of students selected to participate in the pilot, separately for those in the two treatments and the control arms. On average the three groups display similar characteristics, with only 3 tests (out of 66) failing to reject the equality between one of the 13