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

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

Abstract

Height has long been recognised as associated with better outcomes: the question is whether this association is causal. We use children’s genetic variants as instrumental variables (IV) to deal with possible unobserved confounders and examine the effect of child and adolescent height on a wide range of outcomes: academic performance, IQ, self-esteem, symptoms related to depression and behavioural problems, including hyperactivity, emotional, conduct and peer problems. OLS findings show that taller children have higher IQ scores, perform better in school tests, and are less likely to have emotional or peer problems. The IV results differ. They show that taller children have better cognitive performance but, in contrast to the OLS, indicate that taller children are more likely to have behavioural problems. The magnitude of these IV estimates is large. For example, the effect of one standard deviation increase in height on IQ is comparable to the IQ difference for children born approximately 6 months apart within the same school year, while the increase in hyperactivity is comparable to the raw difference in hyperactivity between boys and girls.

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Bibliographic Info

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: Sep 2010
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Handle: RePEc:imp:wpaper:5947

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Cited by:
  1. Stephanie von Hinke Kessler Scholder & George L. Wehby & Sarah Lewis & Luisa Zuccolo, 2014. "Alcohol Exposure In Utero and Child Academic Achievement," NBER Working Papers 19839, National Bureau of Economic Research, Inc.
  2. 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.
  3. Fang, Muriel Zheng, 2014. "Violating the Monotonicity condition for instrumental variable—Dimorphic patterns of gene–behavior association," Economics Letters, Elsevier, vol. 122(1), pages 59-63.

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