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Math Matters: Education Choices and Wage Inequality

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  • 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
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    References listed on IDEAS

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    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.
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    1. History's winners
      by ? in Stumbling and Mumbling on 2014-06-17 19:58:00

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    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.

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    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

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