中国城乡劳动者体重指数与收入关系的贝叶斯半参数分析
Bayesian semiparametric analysis on the relationship between BMI and income for rural and urban workers in China.
作者信息
Feng Lijuan, Munkin Murat
机构信息
School of Internet Economics and Business, Fujian University of Technology, Fuzhou, China.
Department of Economics, University of South Florida, Tampa, FL, USA.
出版信息
J Appl Stat. 2021 Jun 5;49(12):3215-3235. doi: 10.1080/02664763.2021.1935803. eCollection 2022.
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.
本研究采用贝叶斯半参数方法，考察了中国劳动者体重指数（BMI）与收入之间的非线性关系。利用马尔可夫链蒙特卡罗（MCMC）方法来获得后验分布。我们根据性别和居住地区类型，将整个样本分为四个子样本。利用1989年至2011年中国健康与营养调查（CHNS）的纵向数据，我们发现每组劳动者都存在非线性关系，尤其是农村女性。对于农村和城市的女性而言，超重和肥胖与较低的收入相关。然而，对于这两个地区的男性来说，额外的体重并不会导致收入减少。
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