IDEAS home Printed from https://ideas.repec.org/p/fip/fedawp/88475.html
   My bibliography  Save this paper

Decomposing Outcome Differences between HBCU and Non-HBCU Institutions

Author

Listed:

Abstract

This paper investigates differences in outcomes between historically black colleges and universities (HBCU) and traditional college and universities (non-HBCUs) using a standard Oaxaca/Blinder decomposition. This method decomposes differences in observed educational and labor market outcomes between HBCU and non-HBCU students into differences in characteristics (both student and institutional) and differences in how those characteristics translate into differential outcomes. Efforts to control for differences in unobservables between the two types of students are undertaken through inverse-probability weighting and propensity score matching methodologies. We find that differences in student characteristics make the largest contributions to each outcome difference. However, some hope in identifying policy levers comes in the form of how characteristics translate into outcomes. For example, whereas HBCUs appear to be doing a better job helping female graduates parlay their education into higher earnings, non-HBCUs are doing a better job in helping graduates in science, technology, engineering, and mathematics translate their training into higher earnings. Patterns and importance of regressors are similar at different points of the distributions of outcomes.

Suggested Citation

  • Mels de Zeeuw & Sameera Fazili & Julie L. Hotchkiss, 2020. "Decomposing Outcome Differences between HBCU and Non-HBCU Institutions," FRB Atlanta Working Paper 2020-10, Federal Reserve Bank of Atlanta.
    • Handle: RePEc:fip:fedawp:88475
    DOI: 10.29338/wp2020-10
    as

    Download full text from publisher

    File URL: https://www.frbatlanta.org/-/media/documents/research/publications/wp/2020/07/16/10-decomposing-outcome-differences-between-hbcu-non-hbcu-institutions.pdf
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.29338/wp2020-10?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
    ---><---

    References listed on IDEAS

    as
    1. Nicole M. Fortin, 2008. "The Gender Wage Gap among Young Adults in the United States: The Importance of Money versus People," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
    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. de Zeeuw, Mels & Fazili, Sameera & Hotchkiss, Julie L., 2021. "Decomposing differences in Black student graduation rates between HBCU and non-HBCU Institutions: The devil is in the details," Economics Letters, Elsevier, vol. 202(C).

    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. 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.
    2. Cowan, Benjamin & Schwab, Benjamin, 2016. "Employer-sponsored health insurance and the gender wage gap," Journal of Health Economics, Elsevier, vol. 45(C), pages 103-114.
    3. Kaiser, Lutz C., 2014. "The Gender-Career Estimation Gap," IZA Discussion Papers 8185, Institute of Labor Economics (IZA).
    4. Josep Amer-Mestre and Agnès Charpin, 2022. "Gender Differences in Early Occupational Choices: Evidence from Medical Specialty Selection," Economics Working Papers EUI ECO 2022/01, European University Institute.
    5. Brahim Boudarbat & Marie Connolly, 2013. "The gender wage gap among recent post‐secondary graduates in Canada: a distributional approach," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 46(3), pages 1037-1065, August.
    6. Adam Pilny, 2017. "Explaining Differentials in Subsidy Levels Among Hospital Ownership Types in Germany," Health Economics, John Wiley & Sons, Ltd., vol. 26(5), pages 566-581, May.
    7. repec:hal:spmain:info:hdl:2441/3t1fcs7p369jmaalnboqhpgknn is not listed on IDEAS
    8. Dora Gicheva, 2020. "Occupational Social Value and Returns to Long Hours," Economica, London School of Economics and Political Science, vol. 87(347), pages 682-712, July.
    9. Sloczynski, Tymon, 2013. "Population Average Gender Effects," IZA Discussion Papers 7315, Institute of Labor Economics (IZA).
    10. Islam, Asif M. & Amin, Mohammad, 2023. "The gender labor productivity gap across informal firms," World Development, Elsevier, vol. 167(C).
    11. Himmler, Oliver & Koenig, Tobias, 2012. "Self-Evaluations and Performance: Evidence from Adolescence," Hannover Economic Papers (HEP) dp-507, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    12. Chen, Yiu Por (Vincent) & Zhang, Yuan, 2018. "A decomposition method on employment and wage discrimination and its application in urban China (2002–2013)," World Development, Elsevier, vol. 110(C), pages 1-12.
    13. Laurent Gobillon & Dominique Meurs & Sébastien Roux, 2022. "Differences in Positions along a Hierarchy: Counterfactuals Based on an Assignment Model," Annals of Economics and Statistics, GENES, issue 145, pages 29-74.
    14. bunten, devin michelle & Fu, Ellen & Rolheiser, Lyndsey & Severen, Christopher, 2024. "The Problem Has Existed over Endless Years: Racialized Difference in Commuting, 1980–2019," Journal of Urban Economics, Elsevier, vol. 141(C).
    15. Zhu, Rong, 2016. "Wage differentials between urban residents and rural migrants in urban China during 2002–2007: A distributional analysis," China Economic Review, Elsevier, vol. 37(C), pages 2-14.
    16. Stijn Baert & Sunčica Vujić, 2018. "Does it pay to care? Volunteering and employment opportunities," Journal of Population Economics, Springer;European Society for Population Economics, vol. 31(3), pages 819-836, July.
    17. Elif S. Filiz, 2022. "Does it Payoff to be Blond in a Non-Blond Neighborhood? Eye Color, Hair Color, Ethnic Composition and Starting Wages," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 48(1), pages 122-146, January.
    18. Sabine Krueger & Christian Ebner & Daniela Rohrbach-Schmidt, 2024. "Gender Composition and the Symbolic Value of Occupations: New Evidence of a U-shaped Relationship between Gender and Occupational Prestige Based on German Microdata," Work, Employment & Society, British Sociological Association, vol. 38(1), pages 242-261, February.
    19. Sonja C. Kassenboehmer & Mathias G. Sinning, 2014. "Distributional Changes in the Gender Wage Gap," ILR Review, Cornell University, ILR School, vol. 67(2), pages 335-361, April.
    20. Zhang, Li & Sharpe, Rhonda Vonshay & Li, Shi & Darity, William A., 2016. "Wage differentials between urban and rural-urban migrant workers in China," China Economic Review, Elsevier, vol. 41(C), pages 222-233.
    21. Lex Borghans & Bas Ter Weel & Bruce A. Weinberg, 2014. "People Skills and the Labor-Market Outcomes of Underrepresented Groups," ILR Review, Cornell University, ILR School, vol. 67(2), pages 287-334, April.

    More about this item

    Keywords

    HBCU; decomposition; student debt; returns to education; propensity score matching; inverse-probability weighting; quantile regressions;
    All these keywords.

    JEL classification:

    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:fip:fedawp:88475. 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: Rob Sarwark (email available below). General contact details of provider: https://edirc.repec.org/data/frbatus.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.