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Genetic markers as instrumental variables: an application to child fat mass and academic achievement

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  • Stephanie von Hinke Kessler Scholder
  • George Davey Smith
  • Debbie A. Lawlor
  • Carol Propper
  • Frank Windmeijer

    ()
    (Institute for Fiscal Studies and University of Bristol)

Abstract

The use of genetic markers as instrumental variables (IV) is receiving increasing attention from economists. This paper examines the conditions that need to be met for genetic variants to be used as instruments. We combine the IV literature with that from genetic epidemiology, with an application to child adiposity (fat mass, determined by a dual-energy X-ray absorptiometry (DXA) scan) and academic performance. OLS results indicate that leaner children perform slightly better in school tests compared to their more adipose counterparts, but the IV findings show no evidence that fat mass affects academic outcomes.

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Bibliographic Info

Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP03/10.

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Date of creation: Mar 2010
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Handle: RePEc:ifs:cemmap:03/10

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  1. 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.
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  7. 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.
  8. Daniel S. Hamermesh & Jeff E. Biddle, 1993. "Beauty and the Labor Market," NBER Working Papers 4518, National Bureau of Economic Research, Inc.
  9. Robert Kaestner & Michael Grossman, 2008. "Effects of Weight on Children's Educational Achievement," NBER Working Papers 13764, National Bureau of Economic Research, Inc.
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  12. Joshua D. Angrist & Alan B. Krueger, 1990. "Does Compulsory School Attendance Affect Schooling and Earnings?," NBER Working Papers 3572, National Bureau of Economic Research, Inc.
  13. Burkhauser, Richard V. & Cawley, John, 2008. "Beyond BMI: The value of more accurate measures of fatness and obesity in social science research," Journal of Health Economics, Elsevier, vol. 27(2), pages 519-529, March.
  14. Patrick Royston, 2004. "Multiple imputation of missing values," Stata Journal, StataCorp LP, vol. 4(3), pages 227-241, September.
  15. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
  16. J. Gronniger, 2005. "Familial obesity as a proxy for omitted variables in the obesity-mortality relationship," Demography, Springer, vol. 42(4), pages 719-735, November.
  17. John Cawley, 2004. "The Impact of Obesity on Wages," Journal of Human Resources, University of Wisconsin Press, vol. 39(2).
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Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. The Effect of Child Weight on Academic Performance: Evidence using Genetic Markers
    by Kevin Denny in Geary Behaviour Centre on 2009-07-29 14:56:00
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Cited by:
  1. Böckerman, Petri & Bryson, Alex & Viinikainen, Jutta & Hakulinen, Christian & Pulkki-Raback, Laura & Raitakari, Olli, 2014. "Biomarkers and Long-term Labour Market Outcomes: The Case of Creatine," IZA Discussion Papers 8029, Institute for the Study of Labor (IZA).
  2. Jan-Emmanuel De Neve & Nicholas A. Christakis & James H. Fowler & Bruno S. Frey, 2010. "Genes, Economics, and Happiness," CREMA Working Paper Series 2010-24, Center for Research in Economics, Management and the Arts (CREMA).
  3. 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.

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