近三十年來中國隨著社會經濟的快速發展，人們生活質量逐漸提高，營養水準上升，中國肥胖流行率逐年增加，至今已經達到中等開發國家水準，肥胖也成為樂一種流行的疾病。根據之前學者的研究，肥胖可能導致醫療支出增加，預期餘命減少、患病風險增加、身體移動力和功能降低、薪資減少以及社會歧視等等。其中肥胖與薪資的關係十分複雜，在之前學者的研究中有許多不同的結論，性別在這之間扮演了非常重要的角色，對此本文將在前人理論模型的基礎上，用工具變數分量迴歸的方法深入探討肥胖與薪資之間的關係。
本文選用中國家庭營養與健康調查（CHNS）的數據資料，以BMI最為衡量肥胖程度的標準，通過比較3種工具變數的優缺點以及估計上的差異，本文使用社區超重/肥胖率作為工具變數，採用工具變數分量迴歸的方法進行分析。

我們將樣本根據性別和居住地分成多組樣本，再分別進行IV分量迴歸，其中主要的實證結果顯示，BMI對薪資的影響會隨著薪資的不同而改變。對於薪資較低的人，肥胖會產生負向的影響。這是因為薪資低的人一般從事體力勞動，肥胖會不利於他們的工作，導致生產力下降，薪資下降；而對於薪資較高的人而言，他們一般從事的屬於非體力勞動，肥胖不會影響到他們的生產力水準，反而會在他們的工作中起到一定積極的作用。
性別在模型中扮演了非常重要的角色，在男性的實證結果中，我們發現薪資較低的男性肥胖會產生不利的影響，而薪資較高的男性肥胖則是正向的效果，這主要是因為對男性而言肥胖可以給人一種成熟穩重的感覺，在工作中可以帶來積極的作用，從而使薪資上升；

女性的實證結果則與男性有些許不同，女性的BMI隨著薪資水準逐漸上升接近於0，但小於0，說明無論是什麼薪資水準女性肥胖都會對薪資產生負效果，主要原因有兩點：一是職場上存在對女性的社會歧視，通常職場比較偏好身材苗條的女性，所以肥胖會使薪資下降；二是不同於男性，肥胖不會給女性帶來成熟穩重的感覺，因此哪怕薪資再高職位再大，肥胖都不利於女性的薪資增加。

Summary
This paper aims to investigate the impact of obesity on wages in China. The main method used in this paper is IV quantile regression, which will describe the detail of the coefficient in every quantile.

The data are collected from the China Household Health and Nutrition Survey from 1991 to 2011. The variables wages, BMI and the variables include individual characteristics are selected to measure whether they may affect the wages. In addition, the prevalence of overweight/obesity rate is considered as the instrument of BMI.

The result is different when the sample are divided into male and female. For male sample, we found that the trend in the effect of obesity on wages increases from negative to positive as wage rise, which means that obesity produces a negative effect for the low-wages male but positive effect for the high-wages male. And for female sample, obesity is always negatively impact the wages and increase as wage rises. In other words, the negative effect of obesity on wages decrease as the wage rise for the females.

This study implies that workplace is a social discrimination against women and sometimes it shows the eastern characteristics, hence the impact of obesity on wages will be different for both genders.
Key words: obesity, wages, gender, China

Introduction
According to the ten facts of obesity from World Health Organization (WHO), more than 1.4 billion adults were overweight and more than 500 million people were obese in 2008. At least 2.8 million deaths per year can be attributed to overweight or obesity. From 1980 to 2008, the number of obesity has nearly doubled. Obesity has been considered as a problem in high-income countries, moreover, it also becomes a widespread problem in low-income and medium-income countries gradually.

In recent decades, the obesity problem in China is becoming more and more severe with the growth of consumption level. In 1985, male and female adolescents’ overweight/obesity rates were only 0.2% and 0.1% respectively, overweight rate was near 1.5%. It began to increase significantly after 1990. In 2000, overweight / obesity rate for male were as much as 25%, overweight / obesity rate for female also reached 17%, which has been close to the development of national standards.

Some researches had studied the obesity problem in China. Qin and Pan (2016) use the prevalence of overweight/obesity rate as the instrument variable which was powerful and effective and found that obesity will increase 2.46% of whole country medical expenditure. Huang et al. (2016) used the fixed model to investigate the effect of obesity on wages and the result shows that the normal weight women with non-manual job in 2011 made 2.79-2.95 times more than they had in 1991.

Several methods were used to study the obesity effect on wages in China except quantile regression model. Meanwhile, the model will be improved based on the preview research and the IV quantile regression method will be used to study the impact of obesity on wages.

Materials and methods
The data are collected from the China Household Health and Nutrition Survey from 1991 to 2011. The whole samples were divided into nine small samples according to different genders and residences. The dependent variable is log wages and independent variables includes BMI and individual characteristics.

IV quantile regression are used to show the empirical evidence. Compared to OLS, it is more robust and less affected by heteroskedasticity. What’s more, it can observe the effect of obesity in every quantile that will let us know more about the relationship between obesity and wages.

Result and discussion
The main result of the paper is showed in Figure 1. For the all samples, the coefficient of BMI is from negative to positive and rising gradually. That means the obesity would decrease the wages of the poor but increase the wages of the rich. For the male sample, it seems to be no clear trend but we can find that the most coefficients are negative in the low-wages level and positive in high-wages level. Compared to male sample, the female sample has a clear upward trend and each quantile coefficient are negative except for the 0.95 quantile, which means that obesity is detrimental to most women's wages. The main causes for the differences between male and female are: Firstly, other than women, obesity can give men a mature and stable feeling. Secondly, social discrimination against women will lead to career preference for slender women. Therefore, obesity will benefit commercial entertainment and cooperation to raise wages for men who are with higher salaries. While for women, obesity leads to a decline in most women's wages because of social discrimination.

外文文獻
1: Averett, S., and Korenman, S. (1996). The Economic Reality of the Beauty Myth. Journal of Hunan Resources, 31(2):304-30.
2: Andegiorgish, A. K., Wang, J., Zhang, X., Liu, X., and Zhu, H. (2012). Prevalence of overweight, obesity, and associated risk factors among school children and adolescents in Tianjin, China. European journal of pediatrics, 171(4): 697-703.
3: Barsh and Greg, et al. (2000). Biochemical and Genetic Studies of Pigment‐Type Switching. Pigment Cell and Melanoma Research, 13(s8):48-53.
4: Behrman, Jere R., and Mark R. Rosenzweig (2001). The Returns to Increasing Body Weight. Unpublished.
5: Baum, C. L., and Ford, W. F. (2004). The wage effects of obesity: a longitudinal study. Health economics, 13(9)：885-899.
6: Brunner, E. J., Chandola, T., and Marmot, M. G. (2007). Prospective effect of job strain on general and central obesity in the Whitehall II Study. American journal of epidemiology, 165(7)：828-837.
7: Burke, M.A., Heiland, F. (2007). Social dynamic of obesity. Economic Inquiry, 45: 571-591.
8: Brunello, G., and Hombres, B. (2007). Does body weight affect wages? : Evidence from Europe. Economics and Human Biology, 5(1): 1-19.
9: Burkhauser, R.V., Cawley, J. (2008). Beyond BMI: the value of more accurate measure of fatness and obesity in social science research. Journal of Health Economics, 27(2):519-591.
10: Böckerman, P., Cawley, J., Viinikainen, J., Lehtimäki, T., Rovio, S., Seppälä, I., ... and Raitakari, O. (2016). The effect of weight on labor market outcomes: an application of genetic instrumental variables. National Bureau of Economic Research. IZA Discussion Paper No. 9907.
11: Currie J, Cole N. (1993). Welfare and child health: the link between AFDC participation and birth weight. American Economic Review, 83(4): 971–985.
12: Card, D. (1995). Using geographic variation in college proximity to estimate the return to schooling. In Aspects of Labour Market Behavior: Essays in Honour of John Vanderkemp, Christophides LN, Grant EK, Swidinsky R (eds.), University of Toronto Press: Toronto; 201–222
13: Cawley, J. (2004). The impact of obesity on wages. Journal of Human resources, 39(2): 451-474.
14: Cui, Z., Huxley, R., Wu, Y., and Dibley, M. J. (2010). Temporal trends in overweight and obesity of children and adolescents from nine Provinces in China from 1991–2006. Pediatric Obesity, 5(5): 365-374.
15: Cawley, J., Meyerhoefer, C. (2012). The medical care costs of obesity: an instrumental variables approach. Journal of Health Economics, 31(1):219-230
16: Fu, Q., and George, L. K. (2015). Socioeconomic determinants of childhood overweight and obesity in China: the long arm of institutional power. Sociology of health and illness, 37(6): 805-822.
17: Gordon‐Larsen, P., Wang, H., and Popkin, B. M. (2014). Overweight dynamics in Chinese children and adults. Obesity reviews, 15(S1): 37-48.
18: Goldman, D.P., Bhattacharya, J., Mccaffrey, D.F., Duan, N., Leibowitz, A.A., Joyce, G.F., Morton, S.C. (2001). Effect of insurance on mortality in an HIV-positive population in care. Journal of the American Statistical Association, 96: 883–894.
19: Huang, C.C., Yabiku, S.T., Ayers, S.L. et al (2016). The obesity pay gap: gender, body size, and wage inequalities -a longitudinal study of china adults ,1991-2011.Jounal of Population Research, 33: 221.
20: James, W. P. (1995). A public health approach to the problem of obesity. Journal of the International Association for the Study of Obesity, 19: S37-45.
21: Koenker, R., & Machado, J. A. (1999). Goodness of fit and related inference processes for quantile regression. Journal of the American statistical association, 94(448): 1296-1310.
22: Kline, B., Tobias, J. L. (2009). Is the effect of BMI on Wages the Same for Every Body. Journal of applied econometrics, 23：767-793.
23: Morris, S. (2007). The impact of obesity on employment. Labour Economics, 14(3): 413-433.
24: Mi, Y. J., Zhang, B., Wang, H. J., Yan, J., Han, W., Zhao, J., ... & Tian, Q. B. (2015). Prevalence and secular trends in obesity among Chinese adults, 1991− 2011. American journal of preventive medicine, 49(5): 661-669.
25: Pagan, J. A., and Davila, A. (1997). Obesity, occupational attainment, and earnings. Social Science Quarterly, 756-770.
26: Pietiläinen, K. H., Kaprio, J., Rissanen, A., Winter, T., Rimpelä, A., Viken, R. J., and Rose, R. J. (1999). Distribution and heritability of BMI in Finnish adolescents aged 16 y and 17 y: A study of 4884 twins and 2509 singletons. International Journal of Obesity and Related Metabolic Disorders, 23(2).
27: Qin, X., and Pan, J. (2016). The medical cost attributable to obesity and overweight in China: estimation based on longitudinal surveys. Health economics, 25(10), 1291-1311.
28: Register, C. A., and Williams, D. R. (1990). Wage effects of obesity among young workers. Social Science Quarterly, 71(1):130.
29: Sloan, F.A., Picone, G., Taylor, D., Chou, S.Y. (2001). Hospital ownership and cost and quality of care: Is there a dime’s worth of difference? Journal of Health Economics, 20(1): 1–21.
30: Sullivan, P. W., Ghushchyan, V. H., and Ben-Joseph, R. (2008). The impact of obesity on diabetes, hyperlipidemia and hypertension in the United States. Quality of Life Research, 17(8): 1063.
31: Su, C., Zhang, B., Wang, Y. F., Jia, X. F., Xue, H., and Wang, H. J. (2015). Epidemics of overweight and obesity among growing childhood in China between 1997 and 2009: Impact of Family Income, Dietary Intake, and Physical Activity Dynamics. Chinese medical journal, 128(14): 1879.
32: Wang, Y. (2001). Cross-national comparison of childhood obesity: the epidemic and the relationship between obesity and socioeconomic status. International journal of epidemiology, 30(5): 1129-1136..

中文文獻
1：季成葉、孫軍玲、陳天嬌(2004)，“中國學齡兒童青少年1985～2000年超重、肥胖流行趨勢動態分析”中華流行病學雜誌2004年2期。
2：孫良斌、任建超、楊園爭(2015),“勞動者超重的工資效益—基於中國綜合社會調查(CGSS2013)的證據” 華南理工大學學報(社會科學版)2015年12月第17卷第6期。
3：倪國華、張璟、鄭風田(2013), “中國肥胖流行的現狀和趨勢” 中國食物與營養2013年10期。
4：賀媛、趙小蘭、曾強(2015)，“城市成人超重、肥胖、中心性肥胖的流行特徵和相關危險因素分析” 實用預防醫學2015年04期。
5：趙文華(2006)，“中國超重和肥胖造成的相關慢性疾病的經濟負擔研究” 中華流行病學雜誌2006年7月第27卷第7期。
6：裴耀(2014)，“分位數迴歸及其應用” ，華中師範大學數學與統計學院碩士論文。