Abstract
This paper evaluates the influence of the classmates’ age on individual academic achievement. The identification strategy explores a mechanism for the division of classes based on age homogeneity, with cutoff value determined by the Brazilian law of age at school entry. Fuzzy regression discontinuity estimates a local average treatment effect of 2.34 standard deviations favorable to students assigned to class with older peers, in comparison to those allocated to classes with younger classmates. The empirical estimations use a unique educational dataset originated from the Brazilian Ministry of Education, which provides a large information set related to the student’s scholar environment.
Highlights
Many studies investigate the influence of group composition on student outcomes
An interesting group composition is the age homogeneity classrooms, a school policy adopted in several establishments from the public elementary education system in Brazil1
The data comes from a unique educational survey from the Brazilian Ministry of Education (Fundação Joaquim Nabuco [FUNDAJ], 2013). In addition to this introduction, the paper is organized into six additional sections: section two discusses the econometric method and identification strategy; section three presents a descriptive analysis of the database used; section four discusses the class assignment based on age homogeneity used to divide classrooms; section five applies some validity tests to the discontinuous design studied here; section six assembles the results; and the last section gathers the paper’s main conclusions
Summary
Many studies investigate the influence of group composition on student outcomes. On the tracking literature, the concern is to understand if putting together similar individuals turns to be beneficial. Our empirical strategy resembles that of Koppensteiner (2018), our identification strategy presents an advantage over his study: the student’s school achievement is measured twice in a year This longitudinal aspect of academic scores permits to control for preexisting differences between students and allows to separate out own relative age effect from the peer age effects. The data comes from a unique educational survey from the Brazilian Ministry of Education (Fundação Joaquim Nabuco [FUNDAJ], 2013) In addition to this introduction, the paper is organized into six additional sections: section two discusses the econometric method and identification strategy; section three presents a descriptive analysis of the database used; section four discusses the class assignment based on age homogeneity used to divide classrooms; section five applies some validity tests to the discontinuous design studied here; section six assembles the results; and the last section gathers the paper’s main conclusions
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