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Skill, parental income, and IV estimation of the returns to schooling

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  • Robert J. Lemke
  • Isaac C. Rischall

Abstract

Recently, attention has moved away from using parental background variables, such as parental education, in favour of using institutional features of the education system as instruments when estimating the return to schooling. In this paper, these possible instruments are revisited. Using the National Longitudinal Survey of Youth, several specifications of the wage equation are estimated and three types of instruments used - parental education, quarter of birth, and college proximity. It is shown that under some specifications - in particular, by including parental income and individual skill in the wage equation - parental education appears to be a valid and useful instrument. On the other hand, when using the institutional instruments, the weak correlation between the instruments and years of schooling produces imprecise and likely biased estimates of the return to schooling.

Suggested Citation

  • Robert J. Lemke & Isaac C. Rischall, 2003. "Skill, parental income, and IV estimation of the returns to schooling," Applied Economics Letters, Taylor & Francis Journals, vol. 10(5), pages 281-286, April.
    • Handle: RePEc:taf:apeclt:v:10:y:2003:i:5:p:281-286
    DOI: 10.1080/13504850320000078653
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    References listed on IDEAS

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    Cited by:

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    2. Kyunghoon Ban & Désiré Kédagni, 2022. "Nonparametric bounds on treatment effects with imperfect instruments [Instrument-based estimation with binarized treatments: Issues and tests for the exclusion restriction]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 477-493.
    3. Kasey S. Buckles & Daniel M. Hungerman, 2013. "Season of Birth and Later Outcomes: Old Questions, New Answers," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 711-724, July.
    4. Xinxin Ma, 2024. "Union membership and the wage gap between the public and private sectors: evidence from China," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 58(1), pages 1-25, December.
    5. Sanjaya DeSilva & Mohammed Mehrab Bin Bakhtiar, 2011. "Women, Schooling, and Marriage in Rural Philippines," Economics Working Paper Archive wp_701, Levy Economics Institute.
    6. Wied, Dominik, 2024. "Semiparametric distribution regression with instruments and monotonicity," Labour Economics, Elsevier, vol. 90(C).
    7. Tamar Khitarishvili, 2010. "Assessing the Returns to Education in Georgia," Economics Working Paper Archive wp_608, Levy Economics Institute.
    8. Jörg Breitung & Alexander Mayer & Dominik Wied, 2024. "Asymptotic properties of endogeneity corrections using nonlinear transformations," The Econometrics Journal, Royal Economic Society, vol. 27(3), pages 362-383.
    9. Mika Haapanen & Petri Böckerman, 2017. "More educated, more mobile? Evidence from post-secondary education reform," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(1), pages 8-26, January.
    10. Long, Mark C., 2008. "College quality and early adult outcomes," Economics of Education Review, Elsevier, vol. 27(5), pages 588-602, October.
    11. Florence Neymotin, 2014. "How Parental Involvement Affects Childhood Behavioral Outcomes," Journal of Family and Economic Issues, Springer, vol. 35(4), pages 433-451, December.
    12. Rietveld, Cornelius A. & Webbink, Dinand, 2016. "On the genetic bias of the quarter of birth instrument," Economics & Human Biology, Elsevier, vol. 21(C), pages 137-146.

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