肥胖對薪資的影響：多層次交叉分類模型分析

李佩勳

doi:10.6342/NTU201602181

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肥胖对薪资的影响：多层次交叉分类模型分析

The Effect of Obesity and Wage:Cross-Classified Multilevel Analysis

李佩勳 , 硕士　　导师：陈端容　　

繁体中文 DOI： 10.6342/NTU201602181

肥胖；薪资；多阶层；交叉分类模型； Obesity ； Wage ； Multilevel Analysis ； Cross-Classified

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摘要 │ 参考文献 (78) │ 国际计量

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Background: Obesity has grown into a global health issue and caused the huge burden of health and economic. It can have serious impact on a person’s health and results in the labor market. Entering the labor market is an important phase in one’s career. The employers is difficult to judge based on past experience if someone who did not have any working experience. Therefore, the employers will use other messages to determine how many wages to give. For instance, the first impression, education and so on. In addition to the personal ability, the use of social capital as the way to search job can also cause the wage inequality. Thus, this study aimed to examine the effect of obesity, characteristics of personal education and social capital on wages. Moreover, the structures of wages is different from the regions and industries in Taiwan so that it’s worthy of further discussion whether the wage inequality caused by obesity is different from regions and industries.
Methods: The data is mainly based on the Taiwan Education Panel Survey and Taiwan Education Panel Survey and Beyond. We choose the wave 2 of Panel-1 SH which population is from senior/vocational high school and junior college students and the face to face interview follow-up survey of Panel-1 SH to examine the relationship of obesity, characteristics of personal education and social capital on wages. We control gender, wage of the first job, education of father, types of works, weekly working hours, emotion of depression and type of employment in the labor market. We use Cross-Classified Multilevel Analysis to analysis whether the wage inequality caused by obesity is different from regions and industries.
Result: According to the results of the first level, a person’s obesity status from 2003 to 2010 was associated with their wage in the age of 25 or 26. People who became or maintained obesity from 2003 to 2010 had lower wages than those who were non-obese in the same period. People who graduated from university had higher wages than those who graduated from senior or vocational high school. Those who graduated from public school also had higher wages than private school. Cross-Classified Multilevel Analysis shows that wages is different from regions and industries.
Conclusion: Considering the factors of individual, regional and industries, wages in the age of 25 or 26 are affected by obesity. In addition, the educational level and school type also have influence on wages The difference of wages was determinate by the variables of individual level. The major reason might be the population were predominated by novices works. In this population, the wages of entering the workplace affected by personal factors greatly. We suggested that health and enterprise organizations must develop relevant health promotion programs to reduce obesity rates. Multilevel analysis has a key role to clarify the complex issue and explore the relationship between different levels.

参考文献 ( 78 ) 〈TOP〉

Hox, J. J., Moerbeek, M., & van de Schoot, R. (2010). Multilevel analysis: Techniques and applications: Routledge.
连结：
Kalleberg, A. L. (2000). Nonstandard employment relations: Part-time, temporary and contract work. Annu Rev Sociol, 341-365.
连结：
Kim, D. D., & Basu, A. (2016). Estimating the Medical Care Costs of Obesity in the United States: Systematic Review, Meta-Analysis, and Empirical Analysis. Value in Health.
连结：
Lam, D., & Schoeni, R. F. (1993). Effects of Family Background on Earnings and Returns to Schooling: Evidence from Brazil. Journal of Political Economy, 101(4), 710-740.
连结：
Lin, N. (2002). Social capital: A theory of social structure and action (Vol. 19): Cambridge university press.
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引用含有DOI的文献

DOI可强化引用精确性、增强学术圈连结，并给予使用者跨平台的良好使用经验，目前在全世界已有超过五千万个对象申请DOI。 如想对DOI的使用与概念有进一步了解，请参考 （ ） 。

DOI可强化引用精确性、增强学术圈连结，并给予使用者跨平台的良好使用经验，目前在全世界已有超过五千万个对象申请DOI。如想对DOI的使用与概念有进一步了解，请参考（）。