IDEAS home Printed from https://ideas.repec.org/p/ipe/ipetds/0157.html
   My bibliography  Save this paper

Race Discrimination in Brazil: an Analysis of the Age, Period and Cohort Effects

Author

Listed:
  • Maurício Cortez Reis
  • Anna Risi Vianna Crespo

Abstract

Earnings differential between white and black workers present a decreasing trend for younger cohorts in Brazil. We argue in this paper that the reduction in economic discrimination for younger cohorts could have played an important role on this result. Using the Brazilian National Household Sample Survey data [Pesquisa Nacional por Amostra de Domicílios (PNAD)] from 1987 to 2002, the earnings differential by race is decomposed into two parts through the Oaxaca-Blinder methodology: the first one is the characteristic effect and the second is the discrimination term. This decomposition is made for 90 cells defined by cohort and year. After that, the amount of earnings differential due to discrimination term is decomposed into age, period and cohort effects. According to the evidences, the cohort effects are smaller for younger generations, and the age effects present a decreasing trend for older workers. The results show also that periods with high inflation are associated with weaker contribution of discrimination term to earnings differential. Os diferenciais de rendimentos entre brancos e negros apresentam uma tendência decrescente para as coortes mais novas no Brasil. Argumentamos neste artigo que a redução na discriminação para as gerações mais recentes pode ter desempenhado um papel importante para esse resultado. Usando dados da Pesquisa Nacional por Amostra de Domicílios (PNAD) de 1987 a 2002, o diferencial de rendimentos entre raças é decomposto em dois termos através da metodologia de Oaxaca-Blinder: o primeiro é o efeito característica e o segundo é o termo de discriminação. Essa decomposição é implementada para 90 células definidas pela coorte de nascimento e o ano da pesquisa. Em seguida, a parcela do diferencial de rendimentos atribuída ao termo de discriminação é decomposta nos efeitos idade, período e coorte. De acordo com os resultados, os efeitos de coorte são menores para as gerações mais novas, e os efeitos da idade apresentam uma tendência de redução para os trabalhadores mais velhos. As evidências mostram, também, que períodos de alta inflação estão associados com uma menor contribuição do termo de discriminação para o diferencial de rendimentos.

Suggested Citation

  • Maurício Cortez Reis & Anna Risi Vianna Crespo, 2015. "Race Discrimination in Brazil: an Analysis of the Age, Period and Cohort Effects," Discussion Papers 0157, Instituto de Pesquisa Econômica Aplicada - IPEA.
    • Handle: RePEc:ipe:ipetds:0157
    as

    Download full text from publisher

    File URL: http://www.ipea.gov.br/portal/images/stories/PDFs/TDs/ingles/dp_157.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Joseph G. Altonji & Charles R. Pierret, 2001. "Employer Learning and Statistical Discrimination," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 313-350.
    2. Reis, Mauricio Cortez & Camargo, José Márcio, 2007. "Desemprego dos jovens no Brasil: os efeitos da estabilização da inflação em um mercado de trabalho com escassez de informação," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 61(4), July.
    3. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    4. Campante, Filipe R. & Crespo, Anna R. V. & Leite, Phillippe G. P. G., 2004. "Desigualdade Salarial entre Raças no Mercado de Trabalho Urbano Brasileiro: Aspectos Regionais," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 58(2), April.
    5. Henry S. Farber & Robert Gibbons, 1996. "Learning and Wage Dynamics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(4), pages 1007-1047.
    6. Lundberg, Shelly & Startz, Richard, 1998. "On the Persistence of Racial Inequality," Journal of Labor Economics, University of Chicago Press, vol. 16(2), pages 292-323, April.
    7. Angus S. Deaton & Christina Paxson, 1994. "Saving, Growth, and Aging in Taiwan," NBER Chapters, in: Studies in the Economics of Aging, pages 331-362, National Bureau of Economic Research, Inc.
    8. David A. Wise, 1994. "Studies in the Economics of Aging," NBER Books, National Bureau of Economic Research, Inc, number wise94-1, March.
    9. Altonji, Joseph G. & Blank, Rebecca M., 1999. "Race and gender in the labor market," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 48, pages 3143-3259, Elsevier.
    10. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-661, September.
    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. Salardi, Paola & Ñopo, Hugo R., 2009. "Gender and Racial Wage Gaps in Brazil 1996-2006: Evidence Using a Matching Comparisons Approach," IDB Publications (Working Papers) 1649, Inter-American Development Bank.
    2. Gerard, François & Lagos, Lorenzo & Severnini, Edson & Card, David, 2018. "Assortative Matching or Exclusionary Hiring? The Impact of Firm Policies on Racial Wage Differences in Brazil," CEPR Discussion Papers 13273, C.E.P.R. Discussion Papers.

    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. Carlsson, Magnus & Fumarco, Luca & Rooth, Dan-Olof, 2013. "Artifactual Evidence of Discrimination in Correspondence Studies? A Replication of the Neumark Method," IZA Discussion Papers 7619, Institute of Labor Economics (IZA).
    2. Ruzzier, Christian A. & Woo, Marcelo D., 2023. "Discrimination with inaccurate beliefs and confirmation bias," Journal of Economic Behavior & Organization, Elsevier, vol. 210(C), pages 379-390.
    3. Barr & Oduro, Abena, 2000. "Ethnicity and wage determination in Ghana," Policy Research Working Paper Series 2506, The World Bank.
    4. Roland G. Fryer, Jr. & Devah Pager & Jörg L. Spenkuch, 2013. "Racial Disparities in Job Finding and Offered Wages," Journal of Law and Economics, University of Chicago Press, vol. 56(3), pages 633-689.
    5. Bohacek, Radim & Myck, Michal, 2017. "Economic Consequences of Political Persecution," IZA Discussion Papers 11136, Institute of Labor Economics (IZA).
    6. repec:eee:labchp:v:3:y:1999:i:pc:p:3143-3259 is not listed on IDEAS
    7. Luojia Hu & Christopher Taber, 2011. "Displacement, Asymmetric Information, and HeterogeneousHuman Capital," Journal of Labor Economics, University of Chicago Press, vol. 29(1), pages 113-152, January.
    8. J. Michelle Brock & Ralph De Haas, 2023. "Discriminatory Lending: Evidence from Bankers in the Lab," American Economic Journal: Applied Economics, American Economic Association, vol. 15(2), pages 31-68, April.
    9. Morten Størling Hedegaard & Jean-Robert Tyran, 2018. "The Price of Prejudice," American Economic Journal: Applied Economics, American Economic Association, vol. 10(1), pages 40-63, January.
    10. Maarten Vendrik & Christiane Schwieren, 2010. "Identification, screening and stereotyping in labour market discrimination," Journal of Economics, Springer, vol. 99(2), pages 141-171, March.
    11. Tani, Massimiliano, 2017. "Local signals and the returns to foreign education," Economics of Education Review, Elsevier, vol. 61(C), pages 174-190.
    12. Koumenta, Maria & Pagliero, Mario & Rostam-Afschar, Davud, 2020. "Occupational licensing and the gender wage gap," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2020, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    13. Song Han, 2011. "Creditor Learning and Discrimination in Lending," Journal of Financial Services Research, Springer;Western Finance Association, vol. 40(1), pages 1-27, October.
    14. Ross Levine & Alexey Levkov & Yona Rubinstein, 2008. "Racial Discrimination and Competition," NBER Working Papers 14273, National Bureau of Economic Research, Inc.
    15. Mueller, Barbara & Wolter, Stefan C., 2011. "The Consequences of Being Different: Statistical Discrimination and the School-to-Work Transition," IZA Discussion Papers 5474, Institute of Labor Economics (IZA).
    16. Simone Bertoli & Morgane Laouenan & Jérôme Valette, 2022. "Border Apprehensions and Federal Sentencing of Hispanic Citizens in the United States," SciencePo Working papers Main hal-03818735, HAL.
    17. Levine, Ross & Rubinstein, Yona & Levkov, Alexey, 2014. "Bank Deregulation and Racial Inequality in America," Critical Finance Review, now publishers, vol. 3(1), pages 1-48, January.
    18. Eleonora Patacchini & Giuseppe Ragusa & Yves Zenou, 2015. "Unexplored dimensions of discrimination in Europe: homosexuality and physical appearance," Journal of Population Economics, Springer;European Society for Population Economics, vol. 28(4), pages 1045-1073, October.
    19. Romain Aeberhardt & Julien Pouget, 2007. "National Origin Wage Differentials in France. Evidence from Matched Employer-Employee Data"," Working Papers 2007-15, Center for Research in Economics and Statistics.
    20. Akyol, Metin & Neugart, Michael & Pichler, Stefan, 2015. "A tradable employment quota," Labour Economics, Elsevier, vol. 36(C), pages 48-63.
    21. Thierry Baudassé & Rémi Bazillier, 2014. "Gender inequality and emigration: Push factor or selection process?," International Economics, CEPII research center, issue 139, pages 19-47.

    More about this item

    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:ipe:ipetds:0157. 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: Fabio Schiavinatto (email available below). General contact details of provider: https://edirc.repec.org/data/ipeaabr.html .

    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.