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Tracking pupils into adulthood: selective schools and long-term well-being in the 1958 British cohort

Author

Listed:
  • Jones, A.M.;
  • Pastore, C.;
  • Rice, N.;

Abstract

We explore the effect of tracking pupils by ability into different secondary schools on adult health, well-being and labour outcomes in England. We address selection bias by balancing individual pre-treatment characteristics via entropy matching, followed by parametric regressions estimated via OLS and IV approaches. Ability tracking does not affect long-term health and well-being, while it marginally raises hourly wages for low-ability pupils, compared to a mixed-ability system. Cognitive and non-cognitive abilities measured prior to secondary school are more significant and positive predictors of adult outcomes. Particularly, non-cognitive skills may have a protective role for adult health for lower cognitive ability children.

Suggested Citation

  • Jones, A.M.; & Pastore, C.; & Rice, N.;, 2018. "Tracking pupils into adulthood: selective schools and long-term well-being in the 1958 British cohort," Health, Econometrics and Data Group (HEDG) Working Papers 18/32, HEDG, c/o Department of Economics, University of York.
  • Handle: RePEc:yor:hectdg:18/32
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    File URL: https://www.york.ac.uk/media/economics/documents/hedg/workingpapers/1832.pdf
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    References listed on IDEAS

    as
    1. Simon Burgess & Claire Crawford & Lindsey Macmillan, 2017. "Assessing the role of grammar schools in promoting social mobility," DoQSS Working Papers 17-09, Department of Quantitative Social Science - UCL Institute of Education, University College London.
    2. Terza, Joseph V. & Basu, Anirban & Rathouz, Paul J., 2008. "Two-stage residual inclusion estimation: Addressing endogeneity in health econometric modeling," Journal of Health Economics, Elsevier, vol. 27(3), pages 531-543, May.
    3. Joshua D. Angrist, 1998. "Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants," Econometrica, Econometric Society, vol. 66(2), pages 249-288, March.
    4. Andrew Jones & Nigel Rice & Pedro Rosa Dias, 2012. "Quality of schooling and inequality of opportunity in health," Empirical Economics, Springer, vol. 42(2), pages 369-394, April.
    5. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    6. Stéphane Bonhomme & Ulrich Sauder, 2011. "Recovering Distributions in Difference-in-Differences Models: A Comparison of Selective and Comprehensive Schooling," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 479-494, May.
    7. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    8. Andrew M. Jones & Nigel Rice & Pedro Rosa Dias, 2011. "Long-Term Effects of School Quality on Health and Lifestyle: Evidence from Comprehensive Schooling Reforms in England," Journal of Human Capital, University of Chicago Press, vol. 5(3), pages 342-376.
    9. repec:eee:jhecon:v:57:y:2018:i:c:p:1-14 is not listed on IDEAS
    10. Ho, Daniel E. & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2007. "Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference," Political Analysis, Cambridge University Press, vol. 15(03), pages 199-236, June.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    ability tracking; educational reform; well-being; health; entropy balancing; instrumental variables;

    JEL classification:

    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • I1 - Health, Education, and Welfare - - Health
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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