Measuring the Effect of Obesity on Earnings

Xiaoshu HanDepartment of Economcs

Definition

Body Mass Index (BMI) [Weight in Pounds / (Height in Inches)2]*703

Underweight BMI < 18.5Normal Weight 18.5 ≤ BMI ≤ 24.9

Overweight 25 ≤ BMI ≤ 29.9

Obesity BMI > 30

1998

Obesity Trends Among U.S. Adults

2007

1990

No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

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.

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.

Question

• Does obesity affect earnings negatively?

-Less productive -Discrimination

• If yes, by how much?

The model

Two sets of instruments:• a lagged value of BMI • the regional mean BMI

0 1 0 2log( )wage BMI X

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

Table 1: BMI and Earnings by sex and age:

Female (n=7220) Male (n=7575)

BMI Wage Sample (%) Wage Sample (%)

<18.5 14.05 1.84 11.09 0.74

18.5-24.9 15.59 39.60 17.65 27.66

25.0-29.9 14.37 28.16 18.67 43.62

>=30 13.76 30.40 17.43 27.99

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)

BMI Wage Sample(%)

Wage Sample(%)

Wage Sample

(%)

Wage Sample(%)

<18.5 13.35 2.58 11.07 1.06 16.00 1.02 11.14 0.35

18.5-24.9 14.02 43.90 15.83 32.03 17.80 34.82 20.84 22.34

25.0-29.9 12.85 25.97 16.56 41.45 15.79 30.59 20.98 46.25

>=30 12.03 27.55 14.99 25.46 15.32 33.57 19.86 31.6

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

The End

• Any questions?