With our panel of constructed ENLACE data, we merge information on program receipt at the individual level derived from administrative data. We define an individual’s beneficiary status based on the receipt of a PROSPERA scholarship in the sixth grade. Because enrollment in primary school is near universal, we assume that if administrative data shows that a sixth grader was not receiving a PROSPERA grant, that sixth grader lives in a household that does not receive PROSPERA. Our definition thus of beneficiary versus non-beneficiary reflects status in sixth grade and the identification strategy compares sixth grade PROSPERA recipients with sixth grade non-recipients in all the years we study.

One might expect PROSPERA recipients to show higher poverty rates than non-recipients and this would imply lower rates of school enrollment between the groups in the absence of the program. We are fortunate to be able to also merge information on children and their households using Context Questionnaires that were applied to children at the time of the ENLACE application to sixth graders in 2007-2008 and this information provides valuable variables for controlling for differences in characteristics between PROSPERA recipients and non-recipients. The context questionnaires were applied only to a random subsample of schools, so we restrict our analysis to this subsample.

We also have data on characteristics of the schools that are collected using “911” forms, which are administrative forms that are filled out at the level of the school at the beginning and the end of each school year, which we also merge to our data. These data allow us to control for measures of quality and to potentially study if PROSPERA impacts are significantly different when children have access to different quality schools. We also use these variables to control for impacts of available school quality on achievement. The particular variables available varies by school year. We use those variables available at the beginning of our panel, for the school year 2007-2008 to construct the following school level indicators: student/teacher ratio, whether school is “multi-grado” meaning a teacher has more than 1 grade in his/her classroom, teacher education levels (measured by proportion of teachers who obtained their bachelor’s degree of all teachers) and the availability of a computer.

Finally, we merge data at the community level from components of the margination index produced by Conapo based on the 2000 Mexican Population Census. The index is the normalized first principal component of nine locality-level population shares: the share illiterate, the share with less than primary school education, the share without a toilet, the share without electricity, the share without running water, the share without drainage, the share with crowding (few rooms per capita), the share with a dirt floor, and the share without a refrigerator. These indicators are also useful as control variables.

We now turn to a discussion of our methodology. Our methodology is non-experimental in that we derive a comparison group not though randomization but rather by choosing a comparison group that potentially represents a counterfactual for the beneficiary group in the absence of the program. In this study, we compare PROSPERA recipients and non-recipients to estimate program impacts. As we will see below, even when PROSPERA and non-PROSPERA students study in the same school, PROSPERA students typically have a lower socioeconomic status than 11