Empirical BMI-Wage Penalty Function
% Wage difference relative to Normal BMI benchmark (22.5) across estimation strategies
Partitioning the gross disparity into structural sorting, human capital friction, and direct labor market penalty.
| Tenure | Age | Benchmark Pay | Simulated Pay | Annual Gap | Cumul. Wealth Loss |
|---|
Estimating the causal effect of body weight on labor market outcomes is complicated by two major econometric challenges: omitted variable bias (e.g., unobserved family background, discount rates, non-cognitive skills) and reverse causality (low wages causing poorer nutritional health and higher obesity risk).
Cawley (2004) - The Impact of Obesity on Wages
Pioneered biological/genetic instrumental variables (using biological children's or sibling/parental BMI as instruments in NLSY79). Found that a 2 standard deviation increase in weight (~65 lbs for women) decreases wages by ~9-18%, with no statistically significant wage penalty for White or Black men.
Averett & Korenman (1996) - Sibling Fixed Effects
Used sister-pair fixed effects to control for shared genetic background, childhood household socioeconomics, and maternal nutrition. Demonstrated that obese sisters suffer substantial wage disadvantages compared to their normal-weight biological sisters.
Brunello, Michaud & Zheng (2009)
Cross-European panel investigation across 9 countries using genetic variations. Confirmed strong female wage penalties across Western European service sectors, amplified in high customer contact roles.