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Bayesian semiparametric analysis on the relationship between BMI and income for rural and urban workers in China

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  • Lijuan Feng
  • Murat Munkin

Abstract

This study examines the nonlinear relationship between BMI and earnings for workers in China using Bayesian semiparametric methods. Markov chain Monte Carlo (MCMC) methods are used to obtain the posterior distribution. We stratify the whole sample into four subsamples based on gender and type of residence area. Using longitudinal data from the China Health and Nutrition Survey (CHNS) from 1989 to 2011, we find nonlinear relationship for each group of workers, especially for rural females. For females in both rural and urban areas, being overweight and obese is associated with lower earnings. However, for males in both areas, earnings are not penalized for extra weight.

Suggested Citation

  • Lijuan Feng & Murat Munkin, 2022. "Bayesian semiparametric analysis on the relationship between BMI and income for rural and urban workers in China," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(12), pages 3215-3235, September.
    • Handle: RePEc:taf:japsta:v:49:y:2022:i:12:p:3215-3235
    DOI: 10.1080/02664763.2021.1935803
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