Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/124839
Authors: 
Pereira, Joaquim Israel Ribas
Bittencourt, Mauricio
Braga, Bernardo
Year of Publication: 
2015
Series/Report no.: 
55th Congress of the European Regional Science Association: "World Renaissance: Changing roles for people and places", 25-28 August 2015, Lisbon, Portugal
Abstract: 
In recent years, educational issues have been of greater importance in economic analysis. Many papers suggest that education is essential for economic growth as well as an important tool to achieve better equality. These effects have been discussed and confirmed by several researchers, whose papers delineate evidence that education promotes growth, adoption of technologies, increased wages, and additional positive externalities (LANGE and TOPEL; ACEMOGLU and ANGRIST, 2000). As a result, education is primarily considered by governments as a social policy tool. Some of these social policy tools are associated with affirmative action, because their goal is to promote equality by affording better conditions to groups that are initially experiencing worse conditions. The Brazilian case consists of the designation of some proportion of vacancies in university to blacks, native Indians and low-income people. We can number two main reasons commonly used in Brazil to justify affirmative action policy in higher education: a form of historical reparation for blacks, given that Brazil was the largest slave country in the world; and the small share of blacks, Indians and low-income individuals in higher education. This paper intends to contribute to the debate regarding the impact of quotas (social and racial) in the Brazilian higher education system, estimating their impacts on student grades as measured by a specific test ? ENADE ? or the National Survey of Student Performance. We use ENADE 2008 as the main source of data, which comprised 59 courses and surveyed more than 74,000 students. Within the theoretical discussion, we present Su?s Job Reservation Model (2005) and Bishop?s Effort Decision Model (2006); these models include factors such as degree, coursework selection, future wages, and quality of peers, as factors that affect the degree of effort and the human capital accumulation. We use a difference-in-differences (DD) method combined with the propensity score matching (PSM), where the main goal is to control unobservable characteristics that are related to the performance and some selection biases related to the treated group. The results demonstrate that the implementation of quotas negatively and significantly affected majors such as Pedagogy, History and Physics, and positively and significantly affected only Agronomy course.
Subjects: 
social and racial quotas
difference-in-differences estimator
propensity score m
JEL: 
I24
I25
I28
Document Type: 
Conference Paper

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