IDEAS home Printed from https://ideas.repec.org/a/eee/ecoedu/v31y2012i6p861-870.html
   My bibliography  Save this article

The effects of high school math curriculum on college attendance: Evidence from the NLSY97

Author

Listed:
  • Aughinbaugh, Alison

Abstract

Using a sample of youth who graduated from high school in the late 1990s and early 2000s, this paper examines the impact of high school math curriculum on the decision to go to college. Results that control for unobserved differences between students and their families suggest that a more rigorous high school math curriculum is associated with a higher probability of attending college and of attending a 4-year college. The household fixed effect results imply that students who take an advanced academic math curriculum in high school (algebra II or precalculus, trigonometry, or calculus) are about 17 percentage points more likely to go to college and 20 percentage points more likely to start college at a 4-year school by age 21 compared to those students whose highest math class was algebra I or geometry.

Suggested Citation

  • Aughinbaugh, Alison, 2012. "The effects of high school math curriculum on college attendance: Evidence from the NLSY97," Economics of Education Review, Elsevier, vol. 31(6), pages 861-870.
    • Handle: RePEc:eee:ecoedu:v:31:y:2012:i:6:p:861-870
    DOI: 10.1016/j.econedurev.2012.06.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0272775712000726
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econedurev.2012.06.004?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. Levine, Phillip B & Zimmerman, David J, 1995. "The Benefit of Additional High-School Math and Science Classes for Young Men and Women," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 137-149, April.
    2. Thomas Lemieux, 2006. "Postsecondary Education and Increasing Wage Inequality," American Economic Review, American Economic Association, vol. 96(2), pages 195-199, May.
    3. Katz, Lawrence F. & Autor, David H., 1999. "Changes in the wage structure and earnings inequality," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 26, pages 1463-1555, Elsevier.
    4. Petra E. Todd & Jeffrey A. Smith, 2001. "Reconciling Conflicting Evidence on the Performance of Propensity-Score Matching Methods," American Economic Review, American Economic Association, vol. 91(2), pages 112-118, May.
    5. Joseph G. Altonji, 1995. "The Effects of High School Curriculum on Education and Labor Market Outcomes," Journal of Human Resources, University of Wisconsin Press, vol. 30(3), pages 409-438.
    6. Currie, Janet & Stabile, Mark, 2006. "Child mental health and human capital accumulation: The case of ADHD," Journal of Health Economics, Elsevier, vol. 25(6), pages 1094-1118, November.
    7. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    8. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 389-432, August.
    9. Juanna Schrøter Joensen & Helena Skyt Nielsen, 2009. "Is there a Causal Effect of High School Math on Labor Market Outcomes?," Journal of Human Resources, University of Wisconsin Press, vol. 44(1).
    10. Heather Rose & Julian R. Betts, 2004. "The Effect of High School Courses on Earnings," The Review of Economics and Statistics, MIT Press, vol. 86(2), pages 497-513, May.
    11. Goodman, Joshua Samuel, 2012. "The Labor of Division: Returns to Compulsory Math Coursework," Scholarly Articles 9403178, Harvard Kennedy School of Government.
    12. Stephen V. Cameron & James J. Heckman, 2001. "The Dynamics of Educational Attainment for Black, Hispanic, and White Males," Journal of Political Economy, University of Chicago Press, vol. 109(3), pages 455-499, June.
    13. Claudia Goldin & Lawrence F. Katz, 2007. "Long-Run Changes in the Wage Structure: Narrowing, Widening, Polarizing," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 38(2), pages 135-168.
    14. Neal, Derek A & Johnson, William R, 1996. "The Role of Premarket Factors in Black-White Wage Differences," Journal of Political Economy, University of Chicago Press, vol. 104(5), pages 869-895, October.
    15. Altonji, Joseph G & Dunn, Thomas A, 1996. "The Effects of Family Characteristics on the Return to Education," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 692-704, November.
    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. Katja Görlitz & Christina Gravert, 2018. "The effects of a high school curriculum reform on university enrollment and the choice of college major," Education Economics, Taylor & Francis Journals, vol. 26(3), pages 321-336, May.
    2. Tobias Meyer & Stephan L. Thomsen & Heidrun Schneider, 2019. "New Evidence on the Effects of the Shortened School Duration in the German States: An Evaluation of Post‐secondary Education Decisions," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 201-253, November.
    3. Ainoa Aparicio Fenoll & Sarah Zaccagni, 2021. "Gender Mix and Team Performance: Differences between Exogenously and Endogenously Formed Teams," Carlo Alberto Notebooks 646, Collegio Carlo Alberto.
    4. Görlitz, Katja & Gravert, Christina, 2015. "The Effects of Increasing the Standards of the High School Curriculum on School Dropout," IZA Discussion Papers 8766, Institute of Labor Economics (IZA).
    5. Biewen, Martin & Schwerter, Jakob, 2019. "Does More Math in High School Increase the Share of Female STEM Workers? Evidence from a Curriculum Reform," IZA Discussion Papers 12236, Institute of Labor Economics (IZA).
    6. De Groote, Olivier, 2019. "Dynamic Effort Choice in High School: Costs and Benefits of an Academic Track," TSE Working Papers 19-1002, Toulouse School of Economics (TSE), revised Jun 2023.
    7. Fenoll, Ainoa Aparicio & Moscarola, Flavia Coda & Zaccagni, Sarah, 2021. "Mathematics camps: A gift for gifted students?," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 738-751.
    8. Ainoa Aparicio Fenoll & Flavia Coda-Moscarola & Sarah Zaccagni, 2021. "Mathematics Camps: A Gift for Gifted Students," Carlo Alberto Notebooks 647, Collegio Carlo Alberto.
    9. Strazzeri, Maurizio & Oggenfuss, Chantal & Wolter, Stefan C., 2022. "Much Ado about Nothing? School Curriculum Reforms and Students' Educational Trajectories," IZA Discussion Papers 15505, Institute of Labor Economics (IZA).
    10. Nguyen, Hieu, 2019. "How does alcohol access affect transitional adults’ healthy dietary behaviors?," Economics & Human Biology, Elsevier, vol. 35(C), pages 82-95.

    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. De Philippis, Marta, 2016. "STEM graduates and secondary school curriculum: does early exposure to science matter?," LSE Research Online Documents on Economics 67679, London School of Economics and Political Science, LSE Library.
    2. Görlitz, Katja & Gravert, Christina, 2015. "The Effects of Increasing the Standards of the High School Curriculum on School Dropout," IZA Discussion Papers 8766, Institute of Labor Economics (IZA).
    3. Kalena E. Cortes & Joshua S. Goodman & Takako Nomi, 2015. "Intensive Math Instruction and Educational Attainment: Long-Run Impacts of Double-Dose Algebra," Journal of Human Resources, University of Wisconsin Press, vol. 50(1), pages 108-158.
    4. Falch, Torberg & Nyhus, Ole Henning & Strøm, Bjarne, 2014. "Causal effects of mathematics," Labour Economics, Elsevier, vol. 31(C), pages 174-187.
    5. Joshua Goodman, 2019. "The Labor of Division: Returns to Compulsory High School Math Coursework," Journal of Labor Economics, University of Chicago Press, vol. 37(4), pages 1141-1182.
    6. Daniel Kreisman & Kevin Stange, 2020. "Vocational and Career Tech Education in American High Schools: The Value of Depth Over Breadth," Education Finance and Policy, MIT Press, vol. 15(1), pages 11-44, Winter.
    7. Katja Görlitz & Christina Gravert, 2018. "The effects of a high school curriculum reform on university enrollment and the choice of college major," Education Economics, Taylor & Francis Journals, vol. 26(3), pages 321-336, May.
    8. Raquel Fonseca & Marie Mélanie Fontaine & Catherine Haeck, 2021. "Le lien entre les compétences en numératie et les rendements sur le marché du travail au Québec," CIRANO Project Reports 2021rp-11, CIRANO.
    9. Gordon Dahl & Dan-Olof Rooth & Anders Stenberg, 2020. "High School Majors, Comparative (Dis)Advantage, and Future Earnings," NBER Working Papers 27524, National Bureau of Economic Research, Inc.
    10. Koedel, Cory & Tyhurst, Eric, 2012. "Math skills and labor-market outcomes: Evidence from a resume-based field experiment," Economics of Education Review, Elsevier, vol. 31(1), pages 131-140.
    11. Mahdi Gholami & Samuel Muehlemann, 2024. "Math Skills, Selection in Training Firms, and Post-Training Wages," Economics of Education Working Paper Series 0212, University of Zurich, Department of Business Administration (IBW).
    12. Biewen, Martin & Schwerter, Jakob, 2019. "Does More Math in High School Increase the Share of Female STEM Workers? Evidence from a Curriculum Reform," IZA Discussion Papers 12236, Institute of Labor Economics (IZA).
    13. Han Yu & Naci Mocan, 2019. "The Impact of High School Curriculum on Confidence, Academic Success, and Mental and Physical Well-Being of University Students," Journal of Labor Research, Springer, vol. 40(4), pages 428-462, December.
    14. Guy Tchuente, 2016. "High School Human Capital Portfolio and College Outcomes," Journal of Human Capital, University of Chicago Press, vol. 10(3), pages 267-302.
    15. Lisha Agarwal & Giorgio Brunello & Lorenzo Rocco, 2021. "The Pathways to College," Journal of Human Capital, University of Chicago Press, vol. 15(4), pages 554-595.
    16. Lenka Fiala & John Eric Humphries & Juanna Schrøter Joensen & Uditi Karna & John A. List & Gregory F. Veramendi, 2022. "How Early Adolescent Skills and Preferences Shape Economics Education Choices," AEA Papers and Proceedings, American Economic Association, vol. 112, pages 609-613, May.
    17. Dougherty, Shaun M. & Goodman, Joshua S. & Hill, Darryl V. & Litke, Erica G. & Page, Lindsay C., 2017. "Objective course placement and college readiness: Evidence from targeted middle school math acceleration," Economics of Education Review, Elsevier, vol. 58(C), pages 141-161.
    18. Jia, Ning, 2021. "Do stricter high school math requirements raise college STEM attainment?," Economics of Education Review, Elsevier, vol. 83(C).
    19. Cortes, Kalena E. & Goodman, Joshua Samuel & Nomi, Takako, 2015. "Intensive Math Instruction and Educational Attainment," Scholarly Articles 34298862, Harvard Kennedy School of Government.
    20. Goodman, Joshua, 2012. "The Labor of Division: Returns to Compulsory Math Coursework," Working Paper Series rwp12-032, Harvard University, John F. Kennedy School of Government.

    More about this item

    Keywords

    Economics of education; Mathematics; College;
    All these keywords.

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

    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:eee:ecoedu:v:31:y:2012:i:6:p:861-870. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/econedurev .

    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.