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

Author

Listed:
  • Debbie A. Lawlor

    (Institute for Fiscal Studies)

  • Carol Propper

    (Institute for Fiscal Studies and Imperial College London)

  • Stephanie von Hinke

    (Institute for Fiscal Studies and University of Bristol)

  • George Davey Smith

    (Institute for Fiscal Studies)

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.

Suggested Citation

  • Debbie A. Lawlor & Carol Propper & Stephanie von Hinke & George Davey Smith, 2010. "Genetic markers as instrumental variables: an application to child fat mass and academic achievement," CeMMAP working papers CWP03/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:03/10
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    File URL: http://cemmap.ifs.org.uk/wps/cwp0310.pdf
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    References listed on IDEAS

    as
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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 19:56:00

    Citations

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    Cited by:

    1. 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, August.
    2. 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.
    3. Böckerman, Petri & Bryson, Alex & Viinikainen, Jutta & Hakulinen, Christian & Pulkki-Råback, Laura & Raitakari, Olli & Pehkonen, Jaakko, 2017. "Biomarkers and long-term labour market outcomes: The case of creatine," Journal of Economic Behavior & Organization, Elsevier, vol. 142(C), pages 259-274.
    4. Joseph Sabia & Daniel Rees, 2015. "Body weight, mental health capital, and academic achievement," Review of Economics of the Household, Springer, vol. 13(3), pages 653-684, September.
    5. Dawid Philip & Didelez Vanessa, 2012. ""Imagine a Can Opener"--The Magic of Principal Stratum Analysis," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-12, July.
    6. Böckerman, Petri & Bryson, Alex & Viinikainen, Jutta & Hakulinen, Christian & Pulkki-Råback, Laura & Raitakari, Olli & Pehkonen, Jaakko, 2017. "Biomarkers and long-term labour market outcomes: The case of creatine," Journal of Economic Behavior & Organization, Elsevier, vol. 142(C), pages 259-274.
    7. Petri Bockerman & Alex Bryson & Christian Hakulinen & Jaakko Pehkonen & Laura Pulkki-Raback & Olli Raitakari & Jutta Viinikainen, 2014. "Biomarkers and Long-term Market Outcomes: The Case of Creatine," CEP Discussion Papers dp1279, Centre for Economic Performance, LSE.
    8. 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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    More about this item

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health
    • I2 - Health, Education, and Welfare - - Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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