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The Impact of Upper Secondary School Flexibility on Sorting and Educational Outcomes

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  • Berggren, Andrea
  • Jeppsson, Louise

Abstract

This paper estimates the causal impact of an upper secondary curriculum reform in Sweden that increased students’ course-taking flexibility in year 2000. In the most popular upper secondary program, it led to a significant decrease in mandatory mathematics requirements. Using administrative Swedish data, we estimate the causal impact of the reform on tertiary education outcomes and expected earnings using a differences-in-discontinuity identification strategy. The method compares students born immediately before and after the cutoff date. The inclusion of students born in neighboring non-reform cutoff years enables us to disentangle the school starting age effect from the unconfounded effect of the reform. We find no negative effects of the reduced mathematics requirements. Rather, we find a positive effect of the reform on students’ probability of enrolling in, and earning a degree from, tertiary education. Our heterogeneity analysis suggests that relatively disadvantaged students were not negatively affected by the reform.

Suggested Citation

  • Berggren, Andrea & Jeppsson, Louise, 2021. "The Impact of Upper Secondary School Flexibility on Sorting and Educational Outcomes," Economics of Education Review, Elsevier, vol. 81(C).
  • Handle: RePEc:eee:ecoedu:v:81:y:2021:i:c:s0272775721000030
    DOI: 10.1016/j.econedurev.2021.102080
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    1. Marianne Bertrand & Magne Mogstad & Jack Mountjoy, 2021. "Improving Educational Pathways to Social Mobility: Evidence from Norway’s Reform 94," Journal of Labor Economics, University of Chicago Press, vol. 39(4), pages 965-1010.
    2. David S. Lee & Thomas Lemieux, 2010. "Regression Discontinuity Designs in Economics," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 281-355, June.
    3. Peter Fredriksson & Björn Öckert, 2014. "Life‐cycle Effects of Age at School Start," Economic Journal, Royal Economic Society, vol. 124(579), pages 977-1004, September.
    4. Sandra E. Black & Paul J. Devereux & Kjell G. Salvanes, 2011. "Too Young to Leave the Nest? The Effects of School Starting Age," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 455-467, May.
    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. 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.
    7. Juanna Schrøter Joensen & Helena Skyt Nielsen, 2016. "Mathematics and Gender: Heterogeneity in Causes and Consequences," Economic Journal, Royal Economic Society, vol. 126(593), pages 1129-1163, June.
    8. Benoît Rapoport & Claire Thibout, 2018. "Why do boys and girls make different educational choices? The influence of expected earnings and test scores," Post-Print hal-01781858, HAL.
    9. 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.
    10. Malamud, Ofer & Pop-Eleches, Cristian, 2011. "School tracking and access to higher education among disadvantaged groups," Journal of Public Economics, Elsevier, vol. 95(11), pages 1538-1549.
    11. Manudeep Bhuller & Magne Mogstad & Kjell G. Salvanes, 2017. "Life-Cycle Earnings, Education Premiums, and Internal Rates of Return," Journal of Labor Economics, University of Chicago Press, vol. 35(4), pages 993-1030.
    12. Pedro Carneiro & Katrine V. Løken & Kjell G. Salvanes, 2015. "A Flying Start? Maternity Leave Benefits and Long-Run Outcomes of Children," Journal of Political Economy, University of Chicago Press, vol. 123(2), pages 365-412.
    13. Martin Söderström & Roope Uusitalo, 2010. "School Choice and Segregation: Evidence from an Admission Reform," Scandinavian Journal of Economics, Wiley Blackwell, vol. 112(1), pages 55-76, March.
    14. Georg Graetz & Björn Öckert & Oskar Nordström Skans, 2020. "Family Background and the Responses to Higher SAT Scores," CESifo Working Paper Series 8362, CESifo.
    15. 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.
    16. Jerik Hanushek & Dennis Kimko, 2006. "Schooling, Labor-force Quality, and the Growth of Nations," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 1, pages 154-193.
    17. Johannes S. Kunz & Kevin E. Staub, 2016. "Subjective completion beliefs and the demand for post-secondary education," Economics of Education Working Paper Series 0120, University of Zurich, Department of Business Administration (IBW).
    18. 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.
    19. Thomas Buser & Muriel Niederle & Hessel Oosterbeek, 2014. "Gender, Competitiveness, and Career Choices," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(3), pages 1409-1447.
    20. Han Yu & Naci Mocan, 2018. "The Impact of High School Curriculum on Confidence, Academic Success, and Mental and Physical Well-Being of University Students," NBER Working Papers 24573, National Bureau of Economic Research, Inc.
    21. Rapoport, Benoît & Thibout, Claire, 2018. "Why do boys and girls make different educational choices? The influence of expected earnings and test scores," Economics of Education Review, Elsevier, vol. 62(C), pages 205-229.
    22. Benoît Rapoport & Claire Thibout, 2018. "Why do boys and girls make different educational choices? The influence of expected earnings and test scores," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01781858, HAL.
    23. Ofer Malamud & Cristian Pop-Eleches, 2010. "General Education versus Vocational Training: Evidence from an Economy in Transition," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 43-60, February.
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    More about this item

    Keywords

    Educational economics; Upper secondary school curriculum; Course selection; Tertiary education; Returns to education; Reform evaluation; Human capital;
    All these keywords.

    JEL classification:

    • H0 - Public Economics - - General
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

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