1. Measuring the Effect of Obesity on Earnings Xiaoshu Han Department of Economcs

2. Definition Body Mass Index (BMI) [Weight in Pounds / (Height in Inches) 2 ]*703 UnderweightBMI < 18.5 Normal Weight18.5 ≤ BMI ≤ 24.9 Overweight25 ≤ BMI ≤ 29.9 ObesityBMI > 30

3. 1998 Obesity Trends Among U.S. Adults 2007 1990 No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

4. Obesity An estimated 66 million adults in the United States are obese. Being obese substantially raises one’s risk of morbidity from: –Hypertension –Dyslipidemia –Type 2 diabetes –Coronary heart disease –Stroke –Gallbladder disease –Osteoarthritis –Sleep apnea and respiratory problems –Endometrial, breast, prostate and colon cancers.

5. Economics Impact According to a study of national costs attributed to both overweight and obesity, medical expenses accounted for 9.1% of the total U.S. medical expenditures in 1998. Medical expenses for overweight and obesity may have reached as high as $78.5 billion in 1998. Obesity may also have consequences on individual economic outcomes such as earnings and employment.

6. Question Does obesity affect earnings negatively? -Less productive -Discrimination If yes, by how much?

7. The model Two sets of instruments: a lagged value of BMI the regional mean BMI

8. The Data Medical Expenditure Panel Survey: Detailed information on demographic characteristics, health conditions, health status, use of medical care services, charges and payments, health insurance coverage, income, and employment. Panel 7,8,9,10 : data of year 2002 – 2005 Individuals of age over 18 but below 65: 14745 data points

9. Table 1: BMI and Earnings by sex and age: Female (n=7220)Male (n=7575) BMIWageSample (%)WageSample (%) <18.514.051.8411.090.74 18.5-24.915.5939.6017.6527.66 25.0-29.914.3728.1618.6743.62 >=3013.7630.4017.4327.99

10. Table 2: BMI and Earnings by sex and age: 18-40 (n=7956)41-64 (n=6839) Female (n=3797)Male (n=4159)Female (n=3423)Male (n=3416) BMIWageSample (%) WageSample (%) WageSampl e (%) WageSample (%) <18.513.352.5811.071.0616.001.0211.140.35 18.5-24.914.0243.9015.8332.0317.8034.8220.8422.34 25.0-29.912.8525.9716.5641.4515.7930.5920.9846.25 >=3012.0327.5514.9925.4615.3233.5719.8631.6

11. Results Negative impact of obesity on earnings is found for females For every 1 unit increase of BMI, there will be a 0.2 percent decrease of earnings 40-years old woman with a height of 65 inches the obese one: $13.8 per hour the normal weight one: $15 per hour But not for males

12. The End Any questions?