IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v122y2014i1p59-63.html
   My bibliography  Save this article

Violating the Monotonicity condition for instrumental variable—Dimorphic patterns of gene–behavior association

Author

Listed:
  • Fang, Muriel Zheng

Abstract

I document the dimorphic patterns for the association between DAT1 9R9R genotype and measures of risky behaviors including drinking, use of marijuana, cocaine, other drugs, and number of sexual partners. The associations between DAT1 9R9R genotype and risky behaviors are often in opposite signs for females and males, in the National Longitudinal Survey of Adolescent Health (Add Health). This article sensitizes the researcher on the sexual dimorphic pattern of gene–behavior association, and its risk to violate the Monotonicity (no-defiers) condition in applications that use genetic markers as instrumental variables.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecolet:v:122:y:2014:i:1:p:59-63
    DOI: 10.1016/j.econlet.2013.10.038
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176513004850
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2013.10.038?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. von Hinke Kessler Scholder, Stephanie & Davey Smith, George & Lawlor, Debbie A. & Propper, Carol & Windmeijer, Frank, 2013. "Child height, health and human capital: Evidence using genetic markers," European Economic Review, Elsevier, vol. 57(C), pages 1-22.
    2. Edward C. Norton & Euna Han, 2008. "Genetic information, obesity, and labor market outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 17(9), pages 1089-1104, September.
    3. Ding, Weili & Lehrer, Steven F. & Rosenquist, J.Niels & Audrain-McGovern, Janet, 2009. "The impact of poor health on academic performance: New evidence using genetic markers," Journal of Health Economics, Elsevier, vol. 28(3), pages 578-597, May.
    4. 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, August.
    5. Fletcher, Jason M. & Lehrer, Steven F., 2011. "Genetic lotteries within families," Journal of Health Economics, Elsevier, vol. 30(4), pages 647-659, July.
    6. von Hinke Kessler Scholder, Stephanie & Davey Smith, George & Lawlor, Debbie A. & Propper, Carol & Windmeijer, Frank, 2012. "The effect of fat mass on educational attainment: Examining the sensitivity to different identification strategies," Economics & Human Biology, Elsevier, vol. 10(4), pages 405-418.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Barban, Nicola & De Cao, Elisabetta & Oreffice, Sonia & Quintana-Domeque, Climent, 2021. "The effect of education on spousal education: A genetic approach," Labour Economics, Elsevier, vol. 71(C).
    2. 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.
    3. Nicola Barban & Elisabetta De Cao & Sonia Oreffice & Climent Quintana-Domeque, 2016. "Assortative Mating on Education: A Genetic Assessment," Working Papers 2016-034, Human Capital and Economic Opportunity Working Group.
    4. Dixon, Padraig & Hollingworth, William & Harrison, Sean & Davies, Neil M. & Davey Smith, George, 2020. "Mendelian Randomization analysis of the causal effect of adiposity on hospital costs," Journal of Health Economics, Elsevier, vol. 70(C).
    5. George Wehby & Allen Wilcox & Rolv Lie, 2013. "The impact of cigarette quitting during pregnancy on other prenatal health behaviors," Review of Economics of the Household, Springer, vol. 11(2), pages 211-233, June.
    6. von Hinke Kessler Scholder, Stephanie & Davey Smith, George & Lawlor, Debbie A. & Propper, Carol & Windmeijer, Frank, 2012. "The effect of fat mass on educational attainment: Examining the sensitivity to different identification strategies," Economics & Human Biology, Elsevier, vol. 10(4), pages 405-418.
    7. Donna Gilleskie & Euna Han & Edward Norton, 2017. "Disentangling the Contemporaneous and Dynamic Effects of Human and Health Capital on Wages over the Life Cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 25, pages 350-383, April.
    8. Petri Böckerman & John Cawley & Jutta Viinikainen & Terho Lehtimäki & Suvi Rovio & Ilkka Seppälä & Jaakko Pehkonen & Olli Raitakari, 2019. "The effect of weight on labor market outcomes: An application of genetic instrumental variables," Health Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 65-77, January.
    9. Wehby, George L. & Murray, Jeffrey C. & Wilcox, Allen & Lie, Rolv T., 2012. "Smoking and body weight: Evidence using genetic instruments," Economics & Human Biology, Elsevier, vol. 10(2), pages 113-126.
    10. Nicole Black & David W. Johnston & Anna Peeters, 2015. "Childhood Obesity and Cognitive Achievement," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1082-1100, September.
    11. Willage, Barton, 2018. "The effect of weight on mental health: New evidence using genetic IVs," Journal of Health Economics, Elsevier, vol. 57(C), pages 113-130.
    12. Steven F. Lehrer & Weili Ding, 2017. "Are genetic markers of interest for economic research?," IZA Journal of Labor Policy, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 6(1), pages 1-23, December.
    13. Jonas Minet Kinge, 2017. "Waist circumference, body mass index, and employment outcomes," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(6), pages 787-799, July.
    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, August.
    15. Hyeokmoon Kweon & Casper A.P. Burik & Richard Karlsson Linner & Ronald de Vlaming & Aysu Okbay & Daphne Martschenko & Kathryn Paige Harden & Thomas A. DiPrete & Philipp D. Koellinger, 2020. "Genetic Fortune: Winning or Losing Education, Income, and Health," Tinbergen Institute Discussion Papers 20-053/V, Tinbergen Institute, revised 01 Dec 2020.
    16. 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, August.
    17. Olivier Bargain & Jinan Zeidan, 2019. "Heterogeneous effects of obesity on mental health: Evidence from Mexico," Health Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 447-460, April.
    18. Lucas Hafner & Harald Tauchmann & Ansgar Wübker, 2021. "Does moderate weight loss affect subjective health perception in obese individuals? Evidence from field experimental data," Empirical Economics, Springer, vol. 61(4), pages 2293-2333, October.
    19. Fletcher, Jason M. & Lehrer, Steven F., 2009. "The Effect of Adolescent Health on Educational Outcomes: Causal Evidence using ‘Genetic Lotteries’ between Siblings," CLSSRN working papers clsrn_admin-2009-40, Vancouver School of Economics, revised 26 Jun 2009.
    20. Steven F. Lehrer & Weili Ding, 2017. "What is the role for molecular genetic data in public policy?," IZA World of Labor, Institute of Labor Economics (IZA), pages 395-395, October.

    More about this item

    Keywords

    Monotonicity; Genetic instrumental variable; Dimorphic pattern;
    All these keywords.

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:122:y:2014:i:1:p:59-63. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.