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Estimation of a dynamic model of weight

  • Shu Ng

    ()

  • Edward Norton

    ()

  • David Guilkey

    ()

  • Barry Popkin

    ()

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.

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File URL: http://hdl.handle.net/10.1007/s00181-012-0547-7
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Article provided by Springer in its journal Empirical Economics.

Volume (Year): 42 (2012)
Issue (Month): 2 (April)
Pages: 413-443

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Handle: RePEc:spr:empeco:v:42:y:2012:i:2:p:413-443
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  17. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
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