IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/15148.html
   My bibliography  Save this paper

Using Genetic Lotteries within Families to Examine the Causal Impact of Poor Health on Academic Achievement

Author

Listed:
  • Jason M. Fletcher
  • Steven F. Lehrer

Abstract

While there is a well-established, large positive correlation between mental and physical health and education outcomes, establishing a causal link remains a substantial challenge. Building on findings from the biomedical literature, we exploit specific differences in the genetic code between siblings within the same family to estimate the causal impact of several poor health conditions on academic outcomes. We present evidence of large impacts of poor mental health on academic achievement. Further, our estimates suggest that family fixed effects estimators by themselves cannot fully account for the endogeneity of poor health. Finally, our sensitivity analysis suggests that these differences in specific portions of the genetic code have good statistical properties and that our results are robust to reasonable violations of the exclusion restriction assumption.

Suggested Citation

  • Jason M. Fletcher & Steven F. Lehrer, 2009. "Using Genetic Lotteries within Families to Examine the Causal Impact of Poor Health on Academic Achievement," NBER Working Papers 15148, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:15148
    Note: ED HE
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w15148.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Kleibergen, Frank & Paap, Richard, 2006. "Generalized reduced rank tests using the singular value decomposition," Journal of Econometrics, Elsevier, vol. 133(1), pages 97-126, July.
    2. Neumark, David, 1999. "Biases in twin estimates of the return to schooling," Economics of Education Review, Elsevier, vol. 18(2), pages 143-148, April.
    3. Weili Ding & Steven F. Lehrer & J. Niels Rosenquist & Janet Audrain-McGovern, 2006. "The Impact of Poor Health on Education: New Evidence Using Genetic Markers," NBER Working Papers 12304, National Bureau of Economic Research, Inc.
    4. Perri, Timothy J., 1984. "Health status and schooling decisions of young men," Economics of Education Review, Elsevier, vol. 3(3), pages 207-213, June.
    5. Andrew Caplin & Mark Dean, 2008. "Dopamine, Reward Prediction Error, and Economics," The Quarterly Journal of Economics, Oxford University Press, vol. 123(2), pages 663-701.
    6. Currie, Janet & Stabile, Mark, 2006. "Child mental health and human capital accumulation: The case of ADHD," Journal of Health Economics, Elsevier, vol. 25(6), pages 1094-1118, November.
    7. Behrman, Jere R & Taubman, Paul, 1976. "Intergenerational Transmission of Income and Wealth," American Economic Review, American Economic Association, vol. 66(2), pages 436-440, May.
    8. Chou, Shin-Yi & Grossman, Michael & Saffer, Henry, 2004. "An economic analysis of adult obesity: results from the Behavioral Risk Factor Surveillance System," Journal of Health Economics, Elsevier, vol. 23(3), pages 565-587, May.
    9. Fletcher, Jason & Wolfe, Barbara, 2008. "Child mental health and human capital accumulation: The case of ADHD revisited," Journal of Health Economics, Elsevier, vol. 27(3), pages 794-800, May.
    10. Edward C. Norton & Euna Han, 2008. "Genetic information, obesity, and labor market outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 17(9), pages 1089-1104.
    11. Dalton Conley & Rebecca Glauber, 2005. "Parental Educational Investment and Children's Academic Risk: Estimates of the Impact of Sibship Size and Birth Order from Exogenous Variations in Fertility," NBER Working Papers 11302, National Bureau of Economic Research, Inc.
    12. Ding, Weili & Lehrer, Steven F. & Rosenquist, J.Niels & Audrain-McGovern, Janet, 2009. "The impact of poor health on academic performance: New evidence using genetic markers," Journal of Health Economics, Elsevier, vol. 28(3), pages 578-597, May.
    13. Hanushek, Eric A, 1992. "The Trade-Off between Child Quantity and Quality," Journal of Political Economy, University of Chicago Press, vol. 100(1), pages 84-117, February.
    14. Daniel Klepinger & Shelly Lundberg & Robert Plotnick, 1999. "How Does Adolescent Fertility Affect the Human Capital and Wages of Young Women?," Journal of Human Resources, University of Wisconsin Press, vol. 34(3), pages 421-448.
    15. Angrist, Joshua D & Evans, William N, 1998. "Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size," American Economic Review, American Economic Association, vol. 88(3), pages 450-477, June.
    16. Taubman, Paul, 1976. "The Determinants of Earnings: Genetics, Family, and Other Environments; A Study of White Male Twins," American Economic Review, American Economic Association, vol. 66(5), pages 858-870, December.
    17. David Cesarini & Christopher T. Dawes & Magnus Johannesson & Paul Lichtenstein & Björn Wallace, 2009. "Genetic Variation in Preferences for Giving and Risk Taking," The Quarterly Journal of Economics, Oxford University Press, vol. 124(2), pages 809-842.
    18. Edward Miguel & Michael Kremer, 2004. "Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities," Econometrica, Econometric Society, vol. 72(1), pages 159-217, January.
    19. Cragg, John G. & Donald, Stephen G., 1993. "Testing Identifiability and Specification in Instrumental Variable Models," Econometric Theory, Cambridge University Press, vol. 9(02), pages 222-240, April.
    20. Glewwe, Paul & Jacoby, Hanan G, 1995. "An Economic Analysis of Delayed Primary School Enrollment in a Low Income Country: The Role of Early Childhood Nutrition," The Review of Economics and Statistics, MIT Press, vol. 77(1), pages 156-169, February.
    21. Hoyt Bleakley, 2007. "Disease and Development: Evidence from Hookworm Eradication in the American South," The Quarterly Journal of Economics, Oxford University Press, vol. 122(1), pages 73-117.
    22. Gruber, Jonathan & Frakes, Michael, 2006. "Does falling smoking lead to rising obesity?," Journal of Health Economics, Elsevier, vol. 25(2), pages 183-197, March.
    23. Behrman, Jere R & Rosenzweig, Mark R & Taubman, Paul, 1994. "Endowments and the Allocation of Schooling in the Family and in the Marriage Market: The Twins Experiment," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1131-1174, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jan-Emmanuel De Neve & James H. Fowler & Bruno S. Frey, 2010. "Genes, economics, and happiness," IEW - Working Papers 475, Institute for Empirical Research in Economics - University of Zurich.
    2. von Hinke Kessler Scholder S, 2009. "Genetic Markers as Instrumental Variables: An Application to Child Fat Mass and Academic Achievement," Health, Econometrics and Data Group (HEDG) Working Papers 09/25, HEDG, c/o Department of Economics, University of York.
    3. Johnson, Eric & Reynolds, C. Lockwood, 2013. "The effect of household hospitalizations on the educational attainment of youth," Economics of Education Review, Elsevier, vol. 37(C), pages 165-182.
    4. Lundborg, Petter & Nilsson, Anton & Rooth, Dan-Olof, 2014. "Adolescent health and adult labor market outcomes," Journal of Health Economics, Elsevier, vol. 37(C), pages 25-40.
    5. Edward C. Norton & Euna Han, 2008. "Genetic information, obesity, and labor market outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 17(9), pages 1089-1104.
    6. Philip Oreopoulos & Kjell G. Salvanes, 2009. "How large are returns to schooling? Hint: Money isn't everything," NBER Working Papers 15339, National Bureau of Economic Research, Inc.
    7. von Hinke Kessler Scholder, Stephanie & Davey Smith, George & Lawlor, Debbie A. & Propper, Carol & Windmeijer, Frank, 2012. "The effect of fat mass on educational attainment: Examining the sensitivity to different identification strategies," Economics & Human Biology, Elsevier, vol. 10(4), pages 405-418.
    8. Jeffrey Carpenter & Justin Garcia & J. Lum, 2011. "Dopamine receptor genes predict risk preferences, time preferences, and related economic choices," Journal of Risk and Uncertainty, Springer, vol. 42(3), pages 233-261, June.
    9. Eide, Eric R. & Showalter, Mark H., 2011. "Estimating the relation between health and education: What do we know and what do we need to know?," Economics of Education Review, Elsevier, vol. 30(5), pages 778-791, October.
    10. Jeffrey S. DeSimone, 2010. "Sadness, Suicidality and Grades," NBER Working Papers 16239, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:15148. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://edirc.repec.org/data/nberrus.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.