# **5. Data and Sample**

# **5.1. Data**

We exploit different sources of school-level data. We exploit school census data between 2007 and 2011. The school census is conducted annually by MEC-INEP<sup>36</sup> and focuses on basic education offered by both private and public schools. In particular, we exploit data on school characteristics and student enrollments. Our sample includes only schools from the regular educational system. Private schools and schools that were not operating in a given year were excluded from our sample. We also excluded schools offering specialized education for children with disabilities.

We use administrative data from MEC/FNDE<sup>37</sup> to gather information on schools enrolled in _Mais Educação_ between 2008 and 2011. In particular, we identify for each school the program’s total costs, divided into variable costs (e.g., payments to tutors, meals, transportation), fixed costs (e.g., related to inputs/materials and school buildings), and fields of knowledge selected in each school, as well as the number of students enrolled in the program. An important drawback in MEC/FNDE’s dataset is that it provides the year that each school joined _Mais Educação,_ but there is no information on when exactly the program’s activities actually began. In our analysis, we assume a one-year lag between schools’ entering the program and the actual implementation of _Mais Educação._ Nevertheless, it is important to stress that the difference in exposure time among schools can lead to heterogeneous impacts, especially in the short-term analysis.

In addition, we exploit the demographic census, collected by the _Instituto Brasileiro de Geografia e Estatística_ (IBGE) in 2010 and data provided by _Instituto de Pesquisa Econômica Aplicada_ (IPEA), to capture characteristics of the municipalities (IDHM), population, etc.<sup>38</sup> We have information only from the demographic census in 2010, and so we used population estimates for the other analyzed years (2007–11), calculated by IBGE.

We measure educational outcomes using three different data sets. First, we measure student academic achievement in Portuguese and mathematics with a national standardized test, _Prova Brasil_ . _Prova Brasil_ is a census evaluation of public primary school students from the fifth and ninth grades. Implemented in 2005, the evaluation takes place every two years. We thus will exploit the data for 2005, 2007, 2009, and 2011. In our main sample, we exclude schools in rural areas,<sup>39</sup> because it is not possible to gather information about their student scores in _Prova Brasil_ over the analyzed period (2005– 11).<sup>40</sup> Second, to measure the quality of education in a broader way, we use the Basic

> _36_ Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira (INEP).

> 37 Fundo Nacional de Desenvolvimento da Educação (FNDE).

> 38 UNDP Atlas (2013) aggregates census data by municipality, and this dataset will be used in the analysis.

> 39 In the short-term analysis, when estimating the average impacts for the sample of schools that joined the program in 2010, rural schools are included.

> 40 Although in 2005 the sample of schools evaluated in _Prova Brasil_ included only urban schools, with at least 30 students enrolled in each of the grades assessed, from 2007 on some rural public schools started participating in the evaluation, but only students enrolled in the fifth grade. In 2009 _Prova Brasil_ began to

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