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The wages of BMI: Bayesian analysis of a skewed treatment-response model with nonparametric endogeneity

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  • Brendan Kline

    (Department of Economics, Northwestern University, Evanston, IL, USA)

  • Justin L. Tobias

    (Department of Economics, Purdue University, West Lafayette, IN, USA)

Abstract

We generalize the specifications used in previous studies of the effect of body mass index (BMI) on earnings by allowing the potentially endogenous BMI variable to enter the log wage equation nonparametrically. We introduce a Bayesian posterior simulator for fitting our model that permits a nonparametric treatment of the endogenous BMI variable, flexibly accommodates skew in the BMI distribution, and whose implementation requires only Gibbs steps. Using data from the 1970 British Cohort Study, our results indicate the presence of nonlinearities in the relationships between BMI and log wages that differ across men and women, and also suggest the importance of unobserved confounding for our sample of males. Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • Brendan Kline & Justin L. Tobias, 2008. "The wages of BMI: Bayesian analysis of a skewed treatment-response model with nonparametric endogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 767-793.
    • Handle: RePEc:jae:japmet:v:23:y:2008:i:6:p:767-793
    DOI: 10.1002/jae.1028
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    References listed on IDEAS

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