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The Effect of Weight on Labor Market Outcomes: An Application of Genetic Instrumental Variables

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  • Böckerman, Petri

    (University of Jyväskylä)

  • Cawley, John

    (Cornell University)

  • Viinikainen, Jutta

    (Jyväskylä University School of Business and Economics)

  • Lehtimäki, Terho

    (University of Tampere)

  • Rovio, Suvi

    (University of Turku)

  • Seppälä, Ilkka

    (University of Tampere)

  • Pehkonen, Jaakko

    (Jyväskylä University School of Business and Economics)

  • Raitakari, Olli

    (University of Turku)

Abstract

The increase in the prevalence of obesity worldwide has led to great interest in the economic consequences of obesity, but valid and powerful instruments for obesity, which are needed to estimate its causal effects, are rare. This paper contributes to the literature by using a novel instrument: genetic risk score, which reflects the predisposition to higher body mass index across many genetic loci. We estimate IV models of the effect of BMI on labor market outcomes using Finnish data that have many strengths: genetic information, measured body mass index, and administrative earnings records that are free of the problems associated with nonresponse, self-reporting error or top-coding. The first stage of the IV models indicate that genetic risk score is a powerful instrument, and the available evidence from the genetics literature is consistent with instrument validity. The results of the IV models indicate weight reduces earnings and employment and increases social income transfers, although we caution that the results are based on small samples, and are sensitive to specification and subsample.

Suggested Citation

  • Böckerman, Petri & Cawley, John & Viinikainen, Jutta & Lehtimäki, Terho & Rovio, Suvi & Seppälä, Ilkka & Pehkonen, Jaakko & Raitakari, Olli, 2016. "The Effect of Weight on Labor Market Outcomes: An Application of Genetic Instrumental Variables," IZA Discussion Papers 9907, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp9907
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    Cited by:

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    4. Raymundo M. Campos-Vazquez & Roy Nuñez, 2019. "Obesity and labor market outcomes in Mexico/Obesidad y el mercado de trabajo en México," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 34(2), pages 159-196.
    5. Stephanie Coffey & Amy Ellen Schwartz, 2021. "Towering Intellects? Sizing Up the Relationship Between Height and Academic Success," Center for Policy Research Working Papers 244, Center for Policy Research, Maxwell School, Syracuse University.
    6. Cawley, John & Han, Euna & Kim, Jiyoon & Norton, Edward C., 2023. "Genetic nurture in educational attainment," Economics & Human Biology, Elsevier, vol. 49(C).
    7. 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.
    8. Li, Ruxue & Zhang, Yating & Cai, Xue & Luo, Dan & Zhou, Wuai & Long, Tianxue & Zhang, Huijing & Jiang, Hua & Li, Mingzi, 2021. "The nudge strategies for weight loss in adults with obesity and overweight: A systematic review and meta-analysis," Health Policy, Elsevier, vol. 125(12), pages 1527-1535.
    9. Demirgüç-Kunt, Asli & Torre, Iván, 2022. "Measuring human capital in middle income countries," Journal of Comparative Economics, Elsevier, vol. 50(4), pages 1036-1067.
    10. Jiangli Dou & Limin Du & Ken Wang & Hailin Sun & Chenggang Zhang, 2020. "Wage Penalties or Wage Premiums? A Socioeconomic Analysis of Gender Disparity in Obesity in Urban China," IJERPH, MDPI, vol. 17(19), pages 1-20, September.
    11. Anna Sanz-de-Galdeano & Anastasia Terskaya & Angie Upegui, 2020. "Association of a genetic risk score with BMI along the life-cycle: Evidence from several US cohorts," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-19, September.
    12. Li, Wenchao, 2023. "Gender of children and risky health behaviors: Evidence from China," Economic Modelling, Elsevier, vol. 119(C).
    13. Antonio Pacifico, 2023. "Obesity and labour market outcomes in Italy: a dynamic panel data evidence with correlated random effects," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(4), pages 557-574, June.
    14. Young-Joo Kim, 2021. "Heterogeneous Impacts of Body Mass Index on Work Hours," IJERPH, MDPI, vol. 18(18), pages 1-12, September.
    15. 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.
    16. Sanz-de-Galdeano, Anna & Terskaya, Anastasia & Upegui, Angie, 2020. "Association of a Genetic Risk Score with BMI along the Life-Cycle: Evidence from Several US Cohorts," IZA Discussion Papers 13671, Institute of Labor Economics (IZA).
    17. Paolo Nicola Barbieri & Hieu Nguyen, 2022. "Diabetes and Young Adults’ Labor Supply: Evidence from a Novel Instrumental Variable Strategy," Journal of Labor Research, Springer, vol. 43(1), pages 1-23, March.
    18. Christina Hansen Edwards & Johan Håkon Bjørngaard & Jonas Minet Kinge, 2021. "The relationship between body mass index and income: Using genetic variants from HUNT as instrumental variables," Health Economics, John Wiley & Sons, Ltd., vol. 30(8), pages 1933-1949, August.
    19. Böckerman, Petri & Viinikainen, Jutta & Vainiomäki, Jari & Hintsanen, Mirka & Pitkänen, Niina & Lehtimäki, Terho & Pehkonen, Jaakko & Rovio, Suvi & Raitakari, Olli, 2017. "Stature and long-term labor market outcomes: Evidence using Mendelian randomization," Economics & Human Biology, Elsevier, vol. 24(C), pages 18-29.

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    More about this item

    Keywords

    employment; earnings; BMI; obesity; genetic instruments;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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