participate. We attempt to overcome the potential identification issues that may arise from non-random assignment and voluntary participation with two different quasiexperiments, each of which are explained below in more detail.

# **_Matching Analysis_**

The first research strategy builds on the design of the first short-term impact evaluation of the program. This evaluation was based on a non-experimental design that compares eligible households from municipalities covered by the program with potentially eligible households (also classified as _Sisben_ level 1) from selected comparable areas not targeted by the program.<sup>19</sup> We follow different cohorts of children in treatment and control municipalities who were interviewed as part of the baseline survey carried out in 2002 and that could have finished high school during the period 2003-2009. Hence, the location, age and grade of the children at baseline determine their treatment status and length of exposure to the program for the treated. Given that 2003 is the first year in which the program was broadly implemented in the samples for the matching analysis, the pool of treated individuals includes children with program exposure that ranges roughly from one to seven years.<sup>20</sup> A limitation of this research strategy is the lack of baseline measures of the outcome variables, making it difficult to test for differences between groups at the pre-program time. Given that high school graduation and test scores are in reality observed only once for the same child, program

> 19 Municipalities were grouped based on the number of eligible families that reside in each of them to form 639 Primary Sampling Units (PSU). Twenty-five strata were then defined based on geographic location, level of urbanization, number of eligible families, and indexes of quality of life and availability of school and health facilities in the municipality. Fifty PSUs (two within each stratum) corresponding to 57 municipalities targeted by the program were selected and then matched to 50 ―control‖ PSUs (equivalent to 63 municipalities) that were relatively similar to ―treatment‖ PSUs. Matching was done within each stratum and the comparability of both types of PSUs was assessed on the basis of population size and an index of quality of life. Finally, a stratified random sample of eligible households was selected in treatment and matched control municipalities. For more details about the matching process and the stratified random methods followed in the evaluation, see Attanasio and others (2005).

> 20 It would be important to measure how the impacts of the program vary with different years of exposure. However, due to empirical limitations, this marginal impact cannot be properly identified. Despite the fact that the presence of cohorts would induce variation of treatment dosage, the evaluation design used in this paper cannot disentangle the effects of age on the outcomes from those of length of exposure. Conditional on being enrolled in school, older beneficiaries (when they joined the program) have fewer years ahead of them in school, and perhaps, are more likely to be observed finishing high school. If this is the case, shorter length of exposure may be wrongly attributed to higher school completion rates.

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