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Ability, Parental Valuation of Education, and the High School Dropout Decision

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  • Kelly Foley
  • Giovanni Gallipoli
  • David A. Green

Abstract

The probability of dropping out of high school varies considerably with parental education. Using a rich Canadian panel data set, we examine the channels determining this socioeconomic status effect. We estimate an extended version of Carneiro, Hansen and Heckman (2003)’s factor model, incorporating effects from cognitive and noncognitive ability and parental valuation of education (PVE). We find that cognitive ability and PVE have substantial impacts on dropping out and that parental education has little direct effect on dropping out after controlling for these factors. Our results confirm the importance of determinants of ability by age 15 but also indicate an important role for PVE during teenage years.

Suggested Citation

  • Kelly Foley & Giovanni Gallipoli & David A. Green, 2014. "Ability, Parental Valuation of Education, and the High School Dropout Decision," Journal of Human Resources, University of Wisconsin Press, vol. 49(4), pages 906-944.
  • Handle: RePEc:uwp:jhriss:v:49:y:2014:i:4:p:906-944
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    Cited by:

    1. Christofides, Louis N. & Hoy, Michael & Milla, Joniada & Stengos, Thanasis, 2012. "Grades, Aspirations and Post-Secondary Education Outcomes," IZA Discussion Papers 6867, Institute for the Study of Labor (IZA).
    2. 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.
    3. Falch, Torberg & Lujala, Päivi & Strøm, Bjarne, 2013. "Geographical constraints and educational attainment," Regional Science and Urban Economics, Elsevier, vol. 43(1), pages 164-176.
    4. 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.
    5. Donna Feir, 2015. "The Intergenerational Effect of Forcible Assimilation Policy on Education," Department Discussion Papers 1501, Department of Economics, University of Victoria.
    6. Coelli, Michael & Green, David A., 2012. "Leadership effects: school principals and student outcomes," Economics of Education Review, Elsevier, vol. 31(1), pages 92-109.
    7. 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.
    8. 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.
    9. 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.
    10. Eleonora Bertoni & Michele Di Maio & Vasco Molini & Roberto Nisticò, 2018. "Education is Forbidden: The Effect of the Boko Haram Conflict on Education in North-East Nigeria," CSEF Working Papers 495, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.

    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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