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Selection Bias in Educational Transition Models: Theory and Empirical Evidence

Author

Listed:
  • Anders Holm

    (Department of Sociology, University of Copenhagen)

  • Mads Meier Jæger

    (Danish National Centre for Social Research, Copenhagen)

Abstract
Most studies which use Mare’s (1980, 1981) seminal model of educational transitions find that the effect of family background variables decreases across educational transitions. Cameron and Heckman (1998, 2001) have argued that this “waning coefficients” phenomenon might be driven by selection on unobserved variables. This paper, first, analyzes theoretically how selection on unobserved variables leads to waning coefficients and, second, illustrates empirically how selection affects estimates of the effect of family background variables on educational transitions. Our empirical analysis which uses data from the United States, United Kingdom, Denmark, and the Netherlands shows that the effect of family background variables on educational transitions is largely constant across transitions when we control for selection on unobserved variables. We also discuss the inherent difficulties in estimating educational transition models which deal effectively with selection on unobserved variables.

Suggested Citation

  • Anders Holm & Mads Meier Jæger, 2009. "Selection Bias in Educational Transition Models: Theory and Empirical Evidence," CAM Working Papers 2009-05, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    • Handle: RePEc:kud:kuieca:2009_05
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    File URL: http://www.econ.ku.dk/cam/wp0910/2009-05.pdf/
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    References listed on IDEAS

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    1. Stephen V. Cameron & James J. Heckman, 1998. "Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts of American Males," Journal of Political Economy, University of Chicago Press, vol. 106(2), pages 262-333, April.
    2. Charles F. Manski, 1997. "Monotone Treatment Response," Econometrica, Econometric Society, vol. 65(6), pages 1311-1334, November.
    3. Angrist, Joshua D, 2001. "Estimations of Limited Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 2-16, January.
    4. Robert Mare, 1979. "Social background composition and educational growth," Demography, Springer;Population Association of America (PAA), vol. 16(1), pages 55-71, February.
    5. Horowitz, Joel L. & Manski, Charles F., 1998. "Censoring of outcomes and regressors due to survey nonresponse: Identification and estimation using weights and imputations," Journal of Econometrics, Elsevier, vol. 84(1), pages 37-58, May.
    6. Mary Arends-Kuenning & Suzanne Duryea, 2006. "The Effect of Parental Presence, Parents’ Education, and Household Headship on Adolescents’ Schooling and Work in Latin America," Journal of Family and Economic Issues, Springer, vol. 27(2), pages 263-286, June.
    7. Anthony F. Heath & Peter Clifford, 1990. "Class Inequalities in Education in the Twentieth Century," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 153(1), pages 1-16, January.
    8. Van de Ven, Wynand P. M. M. & Van Praag, Bernard M. S., 1981. "The demand for deductibles in private health insurance : A probit model with sample selection," Journal of Econometrics, Elsevier, vol. 17(2), pages 229-252, November.
    9. Colding, Bjorg, 2006. "A dynamic analysis of educational progression of children of immigrants," Labour Economics, Elsevier, vol. 13(4), pages 479-492, August.
    10. Stephen V. Cameron & James J. Heckman, 1998. "Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts," NBER Working Papers 6385, National Bureau of Economic Research, Inc.
    11. Arnaud Chevalier & Gauthier Lanot, 2002. "The Relative Effect of Family Characteristics and Financial Situation on Educational Achievement," Education Economics, Taylor & Francis Journals, vol. 10(2), pages 165-181.
    12. Stephen V. Cameron & James J. Heckman, 2001. "The Dynamics of Educational Attainment for Black, Hispanic, and White Males," Journal of Political Economy, University of Chicago Press, vol. 109(3), pages 455-499, June.
    13. Angrist, Joshua D, 2001. "Estimations of Limited Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 27-28, January.
    14. Lauer, Charlotte, 2003. "Family background, cohort and education: A French-German comparison based on a multivariate ordered probit model of educational attainment," Labour Economics, Elsevier, vol. 10(2), pages 231-251, April.
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    Cited by:

    1. Kaitlin Anderson & Gema Zamarro & Jennifer Steele & Trey Miller, 2021. "Comparing Performance of Methods to Deal With Differential Attrition in Randomized Experimental Evaluations," Evaluation Review, , vol. 45(1-2), pages 70-104, February.
    2. Leslie S. Stratton & Nabanita Datta Gupta & David Reimer & Anders Holm, 2017. "Modeling Enrollment in and Completion of Vocational Education: The Role of Cognitive and Non-cognitive Skills by Program Type," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20172, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
    3. Zakir Husain & Swagata Sarkar, 2011. "Gender Disparities in Educational Trajectories in India: Do Females Become More Robust at Higher Levels?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 101(1), pages 37-56, March.
    4. Stratton Leslie S. & Datta Gupta Nabanita & Reimer David & Holm Anders, 2018. "Modeling Completion of Vocational Education: The Role of Cognitive and Noncognitive Skills by Program Type," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 18(4), pages 1-17, October.

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