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Affirmative Action in Higher Education: Impacts of the National Exam in Brazil

Author

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  • Joaquim Israel Ribas Pereira
  • Mauricio Bittencourt
  • Bernardo Braga

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.

Suggested Citation

  • Joaquim Israel Ribas Pereira & Mauricio Bittencourt & Bernardo Braga, 2015. "Affirmative Action in Higher Education: Impacts of the National Exam in Brazil," ERSA conference papers ersa15p1578, European Regional Science Association.
    • Handle: RePEc:wiw:wiwrsa:ersa15p1578
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    File URL: https://www-sre.wu.ac.at/ersa/ersaconfs/ersa15/e150825aFinal01578.pdf
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    References listed on IDEAS

    as
    1. Bishop, John, 2006. "Drinking from the Fountain of Knowledge: Student Incentive to Study and Learn - Externalities, Information Problems and Peer Pressure," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 2, chapter 15, pages 909-944, Elsevier.
    2. Daron Acemoglu & Joshua Angrist, 2001. "How Large Are Human Capital Externalities? Evidence from Compulsory Schooling Laws," NBER Chapters, in: NBER Macroeconomics Annual 2000, Volume 15, pages 9-74, National Bureau of Economic Research, Inc.
    3. Ravallion, Martin, 2008. "Evaluating Anti-Poverty Programs," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 59, pages 3787-3846, Elsevier.
    4. David Neumark & Harry Holzer, 2000. "Assessing Affirmative Action," Journal of Economic Literature, American Economic Association, vol. 38(3), pages 483-568, September.
    5. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    6. Bertrand, Marianne & Hanna, Rema & Mullainathan, Sendhil, 2010. "Affirmative action in education: Evidence from engineering college admissions in India," Journal of Public Economics, Elsevier, vol. 94(1-2), pages 16-29, February.
    7. Lechner, Michael, 2011. "The Estimation of Causal Effects by Difference-in-Difference Methods," Foundations and Trends(R) in Econometrics, now publishers, vol. 4(3), pages 165-224, November.
    8. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
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    Cited by:

    1. Guilherme Strifezzi Leal & Ã lvaro Choi, 2021. "Racial quotas in higher education and pre-college academic performance: Evidence from Brazil," UB School of Economics Working Papers 2021/411, University of Barcelona School of Economics.

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    More about this item

    Keywords

    social and racial quotas; difference-in-differences estimator; propensity score m;
    All these keywords.

    JEL classification:

    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I25 - Health, Education, and Welfare - - Education - - - Education and Economic Development
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

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