IDEAS home Printed from https://ideas.repec.org/a/spr/joerap/v5y2022i1d10.1007_s41996-021-00080-7.html
   My bibliography  Save this article

Are There Performance Differentials Between Quota and Non-quota Brazilian Students?

Author

Listed:
  • Tatiane Pelegrini

    (PUCRS, Business School)

  • Paola Liziane Silva Braga

    (PUCRS, Business School)

  • Gustavo Saraiva Frio

    (PUCRS, Business School)

  • Marco Túlio Aniceto França

    (PUCRS, Business School)

Abstract

This work investigates the performance differentials between students benefited and not benefited by the affirmative action policy of racial, social, and public education quotas in Brazil. The results were estimated using Oaxaca-Ransom decomposition and the recentered influence function regression model. The data are from the 2016–2018 Student Performance National Exam (Enade). The analysis shows that the performance difference between quota and non-quota students, in the mean, is small and not statistically significant in the upper quantiles, but this difference is high in the lower quantiles. For social and racial quotas specifically, there is a drop in the total performance differential along the distribution, making it insignificant in the upper tail. The quota policy provided access to higher education; however, it may still prove to be insufficient and specific actions directed at lower quintile students are needed in order to reduce performance differentials.

Suggested Citation

  • Tatiane Pelegrini & Paola Liziane Silva Braga & Gustavo Saraiva Frio & Marco Túlio Aniceto França, 2022. "Are There Performance Differentials Between Quota and Non-quota Brazilian Students?," Journal of Economics, Race, and Policy, Springer, vol. 5(1), pages 41-53, March.
  • Handle: RePEc:spr:joerap:v:5:y:2022:i:1:d:10.1007_s41996-021-00080-7
    DOI: 10.1007/s41996-021-00080-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41996-021-00080-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s41996-021-00080-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Saavedra-Chanduví, Jaime & Molinas, José R. & De Barros, Ricardo Paes & Ferreira, Francisco H. G., 2009. "Measuring Inequality of Opportunities in Latin America and the Caribbean," IDB Publications (Books), Inter-American Development Bank, number 361, May.
    2. Fortin, Nicole & Lemieux, Thomas & Firpo, Sergio, 2011. "Decomposition Methods in Economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 1, pages 1-102, Elsevier.
    3. John M. Krieg & Paul Storer, 2006. "How Much Do Students Matter? Applying The Oaxaca Decomposition To Explain Determinants Of Adequate Yearly Progress," Contemporary Economic Policy, Western Economic Association International, vol. 24(4), pages 563-581, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rodrigo Zeidan & Silvio Luiz de Almeida & In'acio B'o & Neil Lewis Jr, 2023. "Racial and income-based affirmative action in higher education admissions: lessons from the Brazilian experience," Papers 2304.13936, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gevrek, Z. Eylem & Seiberlich, Ruben R., 2014. "Semiparametric decomposition of the gender achievement gap: An application for Turkey," Labour Economics, Elsevier, vol. 31(C), pages 27-44.
    2. Boris Kaiser, 2016. "Decomposing differences in arithmetic means: a doubly robust estimation approach," Empirical Economics, Springer, vol. 50(3), pages 873-899, May.
    3. Alina Botezat & Ruben R. Seiberlich, 2013. "Educational performance gaps in Eastern Europe," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 21(4), pages 731-756, October.
    4. Botezat Alina, 2012. "Decomposing The Gap In School Achievement Between Finland And Romania '" Some Methodological Aspects," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 165-171, December.
    5. World Bank Group, 2015. "Governance and Finance Analysis of the Basic Education Sector in Nigeria," World Bank Publications - Reports 23683, The World Bank Group.
    6. Joanna Tyrowicz & Lucas van der Velde, 2017. "When the opportunity knocks: large structural shocks and gender wage gaps," GRAPE Working Papers 2, GRAPE Group for Research in Applied Economics.
    7. Francisco H G Ferreira & Sergio P Firpo & Julián Messina, 2022. "Labor Market Experience and Falling Earnings Inequality in Brazil: 1995–2012," The World Bank Economic Review, World Bank, vol. 36(1), pages 37-67.
    8. Huong Thu Le & Ha Trong Nguyen, 2018. "The evolution of the gender test score gap through seventh grade: new insights from Australia using unconditional quantile regression and decomposition," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 7(1), pages 1-42, December.
    9. Leone Leonida & Marianna Marra & Sergio Scicchitano & Antonio Giangreco & Marco Biagetti, 2020. "Estimating the Wage Premium to Supervision for Middle Managers in Different Contexts: Evidence from Germany and the UK," Work, Employment & Society, British Sociological Association, vol. 34(6), pages 1004-1026, December.
    10. Katie Meara & Francesco Pastore & Allan Webster, 2020. "The gender pay gap in the USA: a matching study," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(1), pages 271-305, January.
    11. Sergio Longobardi & Margherita Maria Pagliuca & Andrea Regoli, 2018. "Can problem-solving attitudes explain the gender gap in financial literacy? Evidence from Italian students’ data," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1677-1705, July.
    12. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    13. Manuel Arellano & Stéphane Bonhomme, 2017. "Quantile Selection Models With an Application to Understanding Changes in Wage Inequality," Econometrica, Econometric Society, vol. 85, pages 1-28, January.
    14. Männasoo, Kadri, 2022. "Working hours and gender wage differentials: Evidence from the American Working Conditions Survey," Labour Economics, Elsevier, vol. 76(C).
    15. Tymon Słoczyński, 2015. "The Oaxaca–Blinder Unexplained Component as a Treatment Effects Estimator," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(4), pages 588-604, August.
    16. Amarante, Verónica & Gómez, Marcela, 2016. "El proceso de formalización en el mercado laboral uruguayo," Estudios y Perspectivas – Oficina de la CEPAL en Montevideo 39859, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    17. James Cloyne & Òscar Jordà & Alan M. Taylor, 2020. "Decomposing the Fiscal Multiplier," Working Paper Series 2020-12, Federal Reserve Bank of San Francisco.
    18. Altay Mussurov & Dena Sholk & G. Reza Arabsheibani, 2019. "Informal employment in Kazakhstan: a blessing in disguise?," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 9(2), pages 267-284, June.
    19. Martínez-Iriarte, Julián & Montes-Rojas, Gabriel & Sun, Yixiao, 2024. "Unconditional effects of general policy interventions," Journal of Econometrics, Elsevier, vol. 238(2).
    20. Sloczynski, Tymon, 2013. "Population Average Gender Effects," IZA Discussion Papers 7315, Institute of Labor Economics (IZA).

    More about this item

    Keywords

    Enade; Affirmative action; Quota Law; Oaxaca-Ransom; RIF-regression;
    All these keywords.

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joerap:v:5:y:2022:i:1:d:10.1007_s41996-021-00080-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.