[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
IDEAS home Printed from https://ideas.repec.org/p/red/sed018/654.html
   My bibliography  Save this paper

Math Matters: Education Choices and Wage Inequality

Author

Listed:
  • Michelle Petersen Rendall

    (Monash University)

  • Andrew Rendall

    (University of Zurich)

Abstract
Standard SBTC is a powerful mechanism in explaining the increasing wage gap between educated and uneducated individuals. However, SBTC cannot explain within-group wage inequality in the US. This paper provides an explanation for the observed intra-college group inequality by showing that the top decile earners’ significant wage growth is underpinned by the link between ex ante ability, math-heavy college majors and highly quantitative occupations. We develop a general equilibrium model with multiple education outcomes, where wages are driven by individuals’ ex ante abilities and acquired math skills. A large portion of within-group and general wage inequality is explained by math-biased technical change (MBTC).

Suggested Citation

  • Michelle Petersen Rendall & Andrew Rendall, 2018. "Math Matters: Education Choices and Wage Inequality," 2018 Meeting Papers 654, Society for Economic Dynamics.
    • Handle: RePEc:red:sed018:654
    as

    Download full text from publisher

    File URL: https://red-files-public.s3.amazonaws.com/meetpapers/2018/paper_654.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Arcidiacono, Peter & Hotz, V. Joseph & Kang, Songman, 2012. "Modeling college major choices using elicited measures of expectations and counterfactuals," Journal of Econometrics, Elsevier, vol. 166(1), pages 3-16.
    2. Paglin, Morton & Rufolo, Anthony M, 1990. "Heterogeneous Human Capital, Occupational Choice, and Male-Female Earnings Differences," Journal of Labor Economics, University of Chicago Press, vol. 8(1), pages 123-144, January.
    3. Pedro Carneiro & James J. Heckman & Edward J. Vytlacil, 2011. "Estimating Marginal Returns to Education," American Economic Review, American Economic Association, vol. 101(6), pages 2754-2781, October.
    4. Ralph Stinebrickner & Todd Stinebrickner, 2014. "Academic Performance and College Dropout: Using Longitudinal Expectations Data to Estimate a Learning Model," Journal of Labor Economics, University of Chicago Press, vol. 32(3), pages 601-644.
    5. Hansen, G D, 1993. "The Cyclical and Secular Behaviour of the Labour Input: Comparing Efficiency Units and Hours Worked," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 71-80, Jan.-Marc.
    6. James J. Heckman & Stefano Mosso, 2014. "The Economics of Human Development and Social Mobility," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 689-733, August.
    7. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    8. Joseph G. Altonji & Erica Blom & Costas Meghir, 2012. "Heterogeneity in Human Capital Investments: High School Curriculum, College Major, and Careers," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 185-223, July.
    9. Pedro Bordalo & Katherine Coffman & Nicola Gennaioli & Andrei Shleifer, 2016. "Stereotypes," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1753-1794.
      • Pedro Bordalo & Katherine Coffman & Nicola Gennaioli & Andrei Shleifer, "undated". "Stereotypes," Working Paper 467407, Harvard University OpenScholar.
      • Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2014. "Stereotypes," NBER Working Papers 20106, National Bureau of Economic Research, Inc.
      • Pedro Bordalo & Katherine Coffman & Nicola Gennaioli & Andrei Shleifer, "undated". "Stereotypes," Working Paper 373306, Harvard University OpenScholar.
      • Pedro Bordalo & Katherine Coffman & Nicola Gennaioli & Andrei Shleifer, 2014. "Stereotypes," Working Paper 200246, Harvard University OpenScholar.
    10. Rothstein, Jesse M, 2004. "College performance predictions and the SAT," Department of Economics, Working Paper Series qt59s4j4m4, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    11. Kjetil Storesletten & Chris I. Telmer & Amir Yaron, 2001. "How Important Are Idiosyncratic Shocks? Evidence from Labor Supply," American Economic Review, American Economic Association, vol. 91(2), pages 413-417, May.
    12. Pedros Silos & Eric Smith, 2015. "Human Capital Portfolios," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 18(3), pages 635-652, July.
    13. Gueorgui Kambourov & Iourii Manovskii, 2009. "Occupational Mobility and Wage Inequality," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(2), pages 731-759.
    14. Ralph Stinebrickner & Todd R. Stinebrickner, 2014. "A Major in Science? Initial Beliefs and Final Outcomes for College Major and Dropout," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(1), pages 426-472.
    15. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    16. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    17. Hendricks, Lutz & Schoellman, Todd, 2014. "Student abilities during the expansion of US education," Journal of Monetary Economics, Elsevier, vol. 63(C), pages 19-36.
    18. John Bound & Michael F. Lovenheim & Sarah Turner, 2010. "Why Have College Completion Rates Declined? An Analysis of Changing Student Preparation and Collegiate Resources," American Economic Journal: Applied Economics, American Economic Association, vol. 2(3), pages 129-157, July.
    19. Thomas Lemieux & David Card, 2001. "Going to College to Avoid the Draft: The Unintended Legacy of the Vietnam War," American Economic Review, American Economic Association, vol. 91(2), pages 97-102, May.
    20. Per Krusell & Lee E. Ohanian & JosÈ-Victor RÌos-Rull & Giovanni L. Violante, 2000. "Capital-Skill Complementarity and Inequality: A Macroeconomic Analysis," Econometrica, Econometric Society, vol. 68(5), pages 1029-1054, September.
    21. Basit Zafar, 2013. "College Major Choice and the Gender Gap," Journal of Human Resources, University of Wisconsin Press, vol. 48(3), pages 545-595.
    22. Joseph G. Altonji & Prashant Bharadwaj & Fabian Lange, 2012. "Changes in the Characteristics of American Youth: Implications for Adult Outcomes," Journal of Labor Economics, University of Chicago Press, vol. 30(4), pages 783-828.
    23. Daron Acemoglu, 2002. "Technical Change, Inequality, and the Labor Market," Journal of Economic Literature, American Economic Association, vol. 40(1), pages 7-72, March.
    24. Bartel, Ann P & Lichtenberg, Frank R, 1987. "The Comparative Advantage of Educated Workers in Implementing New Technology," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 1-11, February.
    25. David H. Autor & Lawrence F. Katz & Alan B. Krueger, 1998. "Computing Inequality: Have Computers Changed the Labor Market?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1169-1213.
    26. Rothstein, J.M.Jesse M., 2004. "College performance predictions and the SAT," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 297-317.
    Full references (including those not matched with items on IDEAS)

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. History's winners
      by ? in Stumbling and Mumbling on 2014-06-17 19:58:00

    Citations

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


    Cited by:

    1. Peter Arcidiacono & Esteban M. Aucejo & V. Joseph Hotz, 2016. "University Differences in the Graduation of Minorities in STEM Fields: Evidence from California," American Economic Review, American Economic Association, vol. 106(3), pages 525-562, March.
    2. Motegi, H. & Nishimura, Y. & Oikawa, M., 2016. "Retirement and Cognitive Decline: Evidence from Global Aging Data," Health, Econometrics and Data Group (HEDG) Working Papers 16/11, HEDG, c/o Department of Economics, University of York.

    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. Michelle Rendall & Andrew Rendall, 2013. "Math Matters: Student Ability, College Majors, and Wage Inequality," 2013 Meeting Papers 1196, Society for Economic Dynamics.
    2. Boneva, Teodora & Golin, Marta & Rauh, Christopher, 2022. "Can perceived returns explain enrollment gaps in postgraduate education?," Labour Economics, Elsevier, vol. 77(C).
    3. David J Deming & Kadeem Noray, 2020. "Earnings Dynamics, Changing Job Skills, and STEM Careers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(4), pages 1965-2005.
    4. Fernando Saltiel, 2019. "What's Math Got to Do With It? Multidimensional Ability and the Gender Gap in STEM," 2019 Meeting Papers 1201, Society for Economic Dynamics.
    5. David Hémous & Morten Olsen, 2022. "The Rise of the Machines: Automation, Horizontal Innovation, and Income Inequality," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(1), pages 179-223, January.
    6. Pi, Jiancai & Zhang, Pengqing, 2018. "Skill-biased technological change and wage inequality in developing countries," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 347-362.
    7. Lee, Jong-Wha & Wie, Dainn, 2015. "Technological Change, Skill Demand, and Wage Inequality: Evidence from Indonesia," World Development, Elsevier, vol. 67(C), pages 238-250.
    8. Ariell Reshef, 2013. "Is Technological Change Biased Towards the Unskilled in Services? An Empirical Investigation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(2), pages 312-331, April.
    9. Rosalia Castellano & Gaetano Musella & Gennaro Punzo, 2019. "Exploring changes in the employment structure and wage inequality in Western Europe using the unconditional quantile regression," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 249-304, May.
    10. Gallego, Francisco A., 2012. "Skill Premium in Chile: Studying Skill Upgrading in the South," World Development, Elsevier, vol. 40(3), pages 594-609.
    11. Tyler Ransom & Esteban Aucejo & Arnaud Maurel & Peter Arcidiacono, 2014. "College Attrition and the Dynamics of Information Revelation," 2014 Meeting Papers 529, Society for Economic Dynamics.
    12. Taniguchi, Hiroya & Yamada, Ken, 2022. "ICT capital–skill complementarity and wage inequality: Evidence from OECD countries," Labour Economics, Elsevier, vol. 76(C).
    13. Kartik B. Athreya & Felicia Ionescu & Urvi Neelakantan & Ivan Vidangos, 2020. "Who Values Access to College?," Richmond Fed Economic Brief, Federal Reserve Bank of Richmond, issue 20-03, pages 1-5, March.
    14. Ariell Reshef, 2013. "Is Technological Change Biased Towards the Unskilled in Services? An Empirical Investigation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(2), pages 312-331, April.
    15. Rajeev Darolia & Cory Koedel, 2018. "High Schools And Students' Initial Colleges And Majors," Contemporary Economic Policy, Western Economic Association International, vol. 36(4), pages 692-710, October.
    16. Florian Brugger & Christian Gehrke, 2017. "The Neoclassical Approach to Induced Technical Change: From Hicks to Acemoglu," Metroeconomica, Wiley Blackwell, vol. 68(4), pages 730-776, November.
    17. Nancy L. Stokey, 2018. "Technology and Skill: Twin Engines of Growth," NBER Working Papers 24570, National Bureau of Economic Research, Inc.
    18. Sebastian Lago Raquel & Federico Biagi, 2018. "The Routine Biased Technical Change hypothesis: a critical review," JRC Research Reports JRC113174, Joint Research Centre.
    19. Natalie Obergruber, 2018. "Microeconometric Analysis of Individual and Institutional Determinants of Education and Occupational Choice," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 80.
    20. Ghosh, Pallab Kumar, 2014. "The contribution of human capital variables to changes in the wage distribution function," Labour Economics, Elsevier, vol. 28(C), pages 58-69.

    More about this item

    JEL classification:

    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E25 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Aggregate Factor Income Distribution
    • I20 - Health, Education, and Welfare - - Education - - - General
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

    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:red:sed018:654. 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: Christian Zimmermann (email available below). General contact details of provider: https://edirc.repec.org/data/sedddea.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.