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Ability, parental valuation of education and the high school dropout decision

Author

Listed:
  • Kelly Foley

    (Institute for Fiscal Studies)

  • Giovanni Gallipoli

    (Institute for Fiscal Studies and University of British Columbia)

  • David A. Green

    (Institute for Fiscal Studies and University of British Colombia)

Abstract

We use a large, rich Canadian micro-level dataset to examine the channels through which family socio-economic status and unobservable characteristics affect children's decisions to drop out of high school. First, we document the strength of observable socio-economic factors: our data suggest that teenage boys with two parents who are themselves high school dropouts have a 16 per cent chance of dropping out, compared to a dropout rate of less than 1 per cent for boys whose parents both have a university degree. We examine the channels through which this socio-economic gradient arises using an extended version of the factor model set out in Carneiro, Hansen, and Heckman (2003). Specifically, we consider the impact of cognitive and non-cognitive ability and the value that parents place on education. Our results support three main conclusions. First, cognitive ability at age 15 has a substantial impact on dropping out. The highest ability individuals are predicted never to drop out regardless of parental education or parental valuation of education. In contrast, the lowest ability teenagers have a probability of dropping out of approximately .36 if their parents have a low valuation of education. Second, parental valuation of education has a substantial impact on medium and low ability teenagers. A low ability teenager has a probability of dropping out of approximately .03 if his parents place a high value on education but .36 if their educational valuation is low. These effects are estimated while conditioning on ability at age 15. Thus, under some assumptions, they reflect parental influences during the upper teenage years and are in addition to any impact they might have in the early childhood years leading up to age 15. Third, parental education has no direct effect on dropping out once we control for ability and parental valuation of education. Overall, our results point to the importance of whatever determines ability at age 15 (including, potentially, early childhood interventions) and of parental valuation of education during the teenage years. Our work also provides a small methodological contribution by extending the standard factor based estimator to allow a more non-linear relationship between the factors and a co-variate of interest. We show that allowing for non-linearities has a substantial impact on estimated effects.

Suggested Citation

  • Kelly Foley & Giovanni Gallipoli & David A. Green, 2009. "Ability, parental valuation of education and the high school dropout decision," IFS Working Papers W09/21, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:ifsewp:09/21
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    Cited by:

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    2. Christofides, Louis N. & Hoy, Michael & Milla, Joniada & Stengos, Thanasis, 2012. "Grades, Aspirations and Post-Secondary Education Outcomes," IZA Discussion Papers 6867, Institute of Labor Economics (IZA).
    3. Iryna Hayduk & Maude Toussaint‐Comeau, 2022. "Determinants of noncognitive skills: Mediating effects of siblings' interaction and parenting quality," Contemporary Economic Policy, Western Economic Association International, vol. 40(4), pages 677-694, October.
    4. Green, David A. & Simard-Duplain, Gaëlle & Sweetman, Arthur & Warburton, William P., 2023. "A Scientific Approach to Addressing Social Issues Using Administrative Data," IZA Policy Papers 199, Institute of Labor Economics (IZA).
    5. Kelly Foley, 2019. "The gender gap in university enrolment: Do parents play a role beyond investing in skills?," Canadian Journal of Economics, Canadian Economics Association, vol. 52(2), pages 441-489, May.
    6. Orazio Attanasio & Lina Cardona-Sosa & Carlos Medina & Costas Meghir & Christian Posso, 2021. "Long Term Effects of Cash Transfer Programs in Colombia," Borradores de Economia 1170, Banco de la Republica de Colombia.
    7. Nicholas Trachter, 2015. "Stepping stone and option value in a model of postsecondary education," Quantitative Economics, Econometric Society, vol. 6(1), pages 223-256, March.
    8. Xu, Hui & Zhang, Zheyuan & Zhao, Zhong, 2023. "Parental socioeconomic status and children’s cognitive ability in China," Journal of Asian Economics, Elsevier, vol. 84(C).
    9. Falch, Torberg & Lujala, Päivi & Strøm, Bjarne, 2013. "Geographical constraints and educational attainment," Regional Science and Urban Economics, Elsevier, vol. 43(1), pages 164-176.
    10. Johannes S. Kunz & Kevin E. Staub, 2016. "Subjective completion beliefs and the demand for post-secondary education," ECON - Working Papers 218, Department of Economics - University of Zurich.
    11. Donna Feir, 2015. "The Intergenerational Effect of Forcible Assimilation Policy on Education," Department Discussion Papers 1501, Department of Economics, University of Victoria.
    12. Coelli, Michael & Green, David A., 2012. "Leadership effects: school principals and student outcomes," Economics of Education Review, Elsevier, vol. 31(1), pages 92-109.
    13. Louis N. Christofides & Michael Hoy & Joniada Milla & Thanasis Stengos, 2012. "The Implication of Peer and Parental Influences on University Attendance: A Gender Comparison," Working Papers 1201, University of Guelph, Department of Economics and Finance.
    14. Hou, Feng & Picot, Garnett, 2013. "Why Immigrant Background Matters for University Participation: A Comparison of Switzerland and Canada," CLSSRN working papers clsrn_admin-2013-50, Vancouver School of Economics, revised 22 Nov 2013.
    15. Falch, Torberg & Strøm, Bjarne, 2013. "Schools, ability, and the socioeconomic gradient in education choices," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 43(C), pages 49-59.
    16. Kunz, Johannes S. & Staub, Kevin E., 2020. "Early subjective completion beliefs and the demand for post-secondary education," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 34-55.
    17. Foley, Kelly, 2017. "The gender gap in university participation: What role do skills and parents play?," CLEF Working Paper Series 8, Canadian Labour Economics Forum (CLEF), University of Waterloo.
    18. Green, David & Kesselman, Jonathan Rhys & Tedds, Lindsay M., 2021. "Covering All the Basics: Reforms for a More Just Society," MPRA Paper 105902, University Library of Munich, Germany.
    19. Garnett Picot & Feng Hou, 2013. "Why Immigrant Background Matters for University Participation: A Comparison of Switzerland and Canada," International Migration Review, Wiley Blackwell, vol. 47(3), pages 612-642, September.
    20. Bertoni, Eleonora & Di Maio, Michele & Molini, Vasco & Nisticò, Roberto, 2019. "Education is forbidden: The effect of the Boko Haram conflict on education in North-East Nigeria," Journal of Development Economics, Elsevier, vol. 141(C).
    21. Patrick Bennett & Kelly Foley & David Green & Kjell G. Salvanes, 2024. "Education and inequality: an international perspective," IFS Working Papers W24/40, Institute for Fiscal Studies.
    22. Lufeyo Chitondo, 2022. "Factors influencing absenteeism in Lower Primary schools of Chibombo District in Central Province of Zambia," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 9(5), pages 40-47, May.
    23. Daniel Gladwell & Gurleen Popli & Aki Tsuchiya, 2022. "Predictors of becoming not in education, employment or training: A dynamic comparison of the direct and indirect determinants," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 485-514, December.

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    More about this item

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J08 - Labor and Demographic Economics - - General - - - Labor Economics Policies
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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