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Child height, health and human capital: evidence using genetic markers

  • von Hinke Kessler Scholder, S
  • Davey Smith, G
  • Lawlor, DA
  • Propper, C
  • Windmeijer, F

Height has long been recognized as being associated with better outcomes: the question is whether this association is causal. We use children's genetic variants as instrumental variables to deal with possible unobserved confounders and examine the effect of child/adolescent height on a wide range of outcomes: academic performance, IQ, self-esteem, depression symptoms and behavioral problems. OLS findings show that taller children have higher IQ, perform better in school, and are less likely to have behavioral problems. The IV results differ: taller girls (but not boys) have better cognitive performance and, in contrast to the OLS, greater height appears to increase behavioral problems.

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Paper provided by Imperial College, London, Imperial College Business School in its series Working Papers with number 5947.

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Date of creation: 01 Jan 2013
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Handle: RePEc:imp:wpaper:5947
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  1. repec:pri:rpdevs:case_and_paxson_early_life_health_w15637 is not listed on IDEAS
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  12. Pyett, Priscilla & Rayner, Jo & Venn, Alison & Bruinsma, Fiona & Werther, George & Lumley, Judith, 2005. "Using hormone treatment to reduce the adult height of tall girls: Are women satisfied with the decision in later years?," Social Science & Medicine, Elsevier, vol. 61(8), pages 1629-1639, October.
  13. von Hinke, Stephanie & Davey Smith, George & Lawlor, Debbie A. & Propper, Carol & Windmeijer, Frank, 2016. "Genetic markers as instrumental variables," Journal of Health Economics, Elsevier, vol. 45(C), pages 131-148.
  14. repec:pri:cheawb:case_and_paxson_early_life_health_w15637.pdf is not listed on IDEAS
  15. repec:pri:cheawb:case_and_paxson_early_life_health_w15637 is not listed on IDEAS
  16. Bound, John & Solon, Gary, 1999. "Double trouble: on the value of twins-based estimation of the return to schooling," Economics of Education Review, Elsevier, vol. 18(2), pages 169-182, April.
  17. Joshua D. Angrist & Kathryn Graddy & Guido W. Imbens, 2000. "The Interpretation of Instrumental Variables Estimators in Simultaneous Equations Models with an Application to the Demand for Fish," Review of Economic Studies, Oxford University Press, vol. 67(3), pages 499-527.
  18. Patrick Royston, 2004. "Multiple imputation of missing values," Stata Journal, StataCorp LP, vol. 4(3), pages 227-241, September.
  19. 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.
  20. Nicola Persico & Andrew Postlewaite & Dan Silverman, 2001. "The Effect of Adolescent Experience on Labor Market Outcomes: The Case of Height, Third Version," PIER Working Paper Archive 04-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 05 Jan 2004.
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