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Estimation of a Dynamic Model of Weight

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  • Shu Wen Ng
  • Edward C. Norton
  • David K. Guilkey
  • Barry M. Popkin

Abstract

The ongoing debate about the economic causes of obesity has focused on the changing relative prices of diet and exercise. This paper uses a model that explicitly includes time and spatially varying community-level urbanicity and price measures as instruments to obtain statistically correct measures for the endogenous effects of diet, physical activity, drinking, and smoking on weight. We apply a dynamic panel system GMM estimation model to longitudinal (1991-2006) data from China to model weight and find that among adult men in China, about 6.1% of weight gain was due to declines in physical activity and 2.9-3.8% was due to dietary changes over this period. In the long run, physical activity can account for around 6.9% of weight gain, while diet can account for 3.2-4.2% of weight gain.

Suggested Citation

  • Shu Wen Ng & Edward C. Norton & David K. Guilkey & Barry M. Popkin, 2010. "Estimation of a Dynamic Model of Weight," NBER Working Papers 15864, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:15864
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    1. Aldy, Joseph E., 2014. "The Labor Market Impacts of the 2010 Deepwater Horizon Oil Spill and Offshore Oil Drilling Moratorium," RFF Working Paper Series dp-14-27, Resources for the Future.
    2. Tafreschi, Darjusch, 2015. "The income body weight gradients in the developing economy of China," Economics & Human Biology, Elsevier, vol. 16(C), pages 115-134.
    3. Leonardo Fabio Morales & Penny Gordon-Larsen & David Guilkey, 2014. "Obesity and Health-Related Decisions: An Empirical Model of the Determinants of Weight Status," Borradores de Economia 12171, Banco de la Republica.
    4. Morales, Leonardo Fabio & Gordon-Larsen, Penny & Guilkey, David, 2016. "Obesity and health-related decisions: An empirical model of the determinants of weight status across the transition from adolescence to young adulthood," Economics & Human Biology, Elsevier, vol. 23(C), pages 46-62.
    5. Pinkston, Joshua C., 2017. "The dynamic effects of obesity on the wages of young workers," Economics & Human Biology, Elsevier, vol. 27(PA), pages 154-166.
    6. Daouli, Joan & Davillas, Apostolos & Demoussis, Michael & Giannakopoulos, Nicholas, 2013. "The determinants of body mass in Greece: Evidence from the National Health Survey," MPRA Paper 66392, University Library of Munich, Germany.
    7. Nancy Kong & Weina Zhou, 2021. "The curse of modernization? Western fast food and Chinese children's weight," Health Economics, John Wiley & Sons, Ltd., vol. 30(10), pages 2345-2366, September.
    8. Roemling, Cornelia & Qaim, Matin, 2012. "Obesity Trends, Determinants and Policy Implications in Indonesia," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126208, International Association of Agricultural Economists.
    9. Fadaeenejad, M. & Radzi, M.A.M. & AbKadir, M.Z.A. & Hizam, H., 2014. "Assessment of hybrid renewable power sources for rural electrification in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 299-305.
    10. Leonardo Fabio Morales & Penny Gordon-Larsen & David Guilkey, 2014. "Obesity and Health-Related Decisions: An Empirical Model of the Determinants of Weight Status," Borradores de Economia 846, Banco de la Republica de Colombia.
    11. repec:plo:pone00:0169577 is not listed on IDEAS
    12. Daouli, Joan & Davillas, Apostolos & Demoussis, Michael & Giannakopoulos, Nicholas, 2014. "Obesity persistence and duration dependence: Evidence from a cohort of US adults (1985–2010)," Economics & Human Biology, Elsevier, vol. 12(C), pages 30-44.
    13. Meliyanni Johar & Shiko Maruyama & Jeffrey Truong, 2017. "The contribution of Western fast food to fast-growing body mass in China," Applied Economics, Taylor & Francis Journals, vol. 49(8), pages 797-811, February.

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    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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