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The effect of fat mass on educational attainment: Examining the sensitivity to different identification strategies

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

The literature that examines the relationship between child or adolescent Body Mass Index (BMI) and academic attainment generally finds mixed results. This may be due to the use of different data sets, conditioning variables, or methodologies: studies either use an individual fixed effects (FE) approach and/or an instrumental variable (IV) specification. Using one common dataset, the Avon Longitudinal Study of Parents and Children, and a common set of controls, this paper compares the different approaches (including using different types of IV's), discusses their appropriateness, and contrasts their findings. We show that, although the results differ depending on the approach, most estimates cannot be statistically distinguished from OLS, nor from each other. Examining the potential violations of key assumptions of the different approaches and comparing their point estimates, we conclude that fat mass is unlikely to be causally related to academic achievement in adolescence.

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Article provided by Elsevier in its journal Economics & Human Biology.

Volume (Year): 10 (2012)
Issue (Month): 4 ()
Pages: 405-418

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Handle: RePEc:eee:ehbiol:v:10:y:2012:i:4:p:405-418
Contact details of provider: Web page: http://www.elsevier.com/locate/inca/622964

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  1. Kaestner, Robert & Grossman, Michael, 2009. "Effects of weight on children's educational achievement," Economics of Education Review, Elsevier, vol. 28(6), pages 651-661, December.
  2. von Hinke Kessler Scholder, S & Davey Smith, G & Lawlor, DA & Propper, C & Windmeijer, F, 2010. "Child height, health and human capital: evidence using genetic markers," Working Papers 5947, Imperial College, London, Imperial College Business School.
  3. John Cawley & Richard V. Burkhauser, 2006. "Beyond BMI: The Value of More Accurate Measures of Fatness and Obesity in Social Science Research," NBER Working Papers 12291, National Bureau of Economic Research, Inc.
  4. John Cawley, 2004. "The Impact of Obesity on Wages," Journal of Human Resources, University of Wisconsin Press, vol. 39(2).
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  6. Susan Averett & David Stifel, 2010. "Race and gender differences in the cognitive effects of childhood overweight," Applied Economics Letters, Taylor & Francis Journals, vol. 17(17), pages 1673-1679.
  7. Anne Case & Christina Paxson, 2006. "Stature and status: Height, ability, and labor market outcomes," Working Papers 27, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing..
  8. Fletcher, Jason M. & Lehrer, Steven F., 2011. "Genetic lotteries within families," Journal of Health Economics, Elsevier, vol. 30(4), pages 647-659, July.
  9. Edward C Norton & Euna Han, 2007. "Genetic Information, Obesity, and Labor Market Outcomes," Health, Econometrics and Data Group (HEDG) Working Papers 07/15, HEDG, c/o Department of Economics, University of York.
  10. John Cawley & C. Katharina Spiess, 2008. "Obesity and Skill Attainment in Early Childhood," NBER Working Papers 13997, National Bureau of Economic Research, Inc.
  11. Hamermesh, Daniel S & Biddle, Jeff E, 1994. "Beauty and the Labor Market," American Economic Review, American Economic Association, vol. 84(5), pages 1174-94, December.
  12. Joseph J. Sabia, 2007. "The Effect of Body Weight on Adolescent Academic Performance," Southern Economic Journal, Southern Economic Association, vol. 73(4), pages 871–900, April.
  13. Cawley, John & Meyerhoefer, Chad, 2012. "The medical care costs of obesity: An instrumental variables approach," Journal of Health Economics, Elsevier, vol. 31(1), pages 219-230.
  14. Stephanie von Hinke Kessler Scholder & George Davey Smith & Debbie A. Lawlor & Carol Propper & Frank Windmeijer, 2011. "Mendelian randomization: the use of genes in instrumental variable analyses," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 893-896, 08.
  15. John Cawley & Euna Han & Edward C. Norton, 2011. "The validity of genes related to neurotransmitters as instrumental variables," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 884-888, 08.
  16. 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.
  17. Angrist, Joshua D & Graddy, Kathryn & Imbens, Guido W, 2000. "The Interpretation of Instrumental Variables Estimators in Simultaneous Equations Models with an Application to the Demand for Fish," Review of Economic Studies, Wiley Blackwell, vol. 67(3), pages 499-527, July.
  18. Stephanie von Hinke Kessler Scholder & George Davey Smith & Debbie A. Lawlor & Carol Propper & Frank Windmeijer, 2011. "Genetic Markers as Instrumental Variables," The Centre for Market and Public Organisation 11/274, Department of Economics, University of Bristol, UK.
  19. Jason M. Fletcher, 2011. "The promise and pitfalls of combining genetic and economic research," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 889-892, 08.
  20. Burkhauser, Richard V. & Cawley, John & Schmeiser, Maximilian D., 2009. "The timing of the rise in U.S. obesity varies with measure of fatness," Economics & Human Biology, Elsevier, vol. 7(3), pages 307-318, December.
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