Working Paper: NBER ID: w21992
Authors: Partha Deb; Carmen Vargas
Abstract: This study uses county-level variation in implementation of calorie labeling laws in the US to identify the effects of such laws on body mass. Using the 2003 to 2012 waves of the Behavioral Risk Factor Surveillance System, we find a statistically insignificant average treatment effect for women and a small, statistically significant and negative average treatment effect for men, indicating a decrease in BMI after implementation of calorie-labeling laws. We estimate finite mixture models and discover that the average treatment effects mask substantial heterogeneity in the effects across three classes of women and men. For both women and men, the three classes, determined within the model, can be described as a subpopulation with normal weight, a second one that is overweight on average and a third one that is obese on average. Estimates from finite mixture models show that the effect is largely concentrated among a class of women with BMI distributions centered on overweight. The effects for men are statistically significant for each of the three classes and large for men in the overweight and obese classes. These results suggest that overweight and obese individuals are especially sensitive to relevant information.
Keywords: Calorie Labeling; Body Mass Index; Public Health; Heterogeneous Effects
JEL Codes: I12; I18
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Entropy balancing (D50) | comparability between treatment and control groups (C90) |
| Calorie labeling laws (D18) | BMI (women) (J16) |
| Calorie labeling laws (D18) | BMI (men) (L83) |
| Calorie labeling laws (D18) | BMI (overweight men) (I12) |
| Calorie labeling laws (D18) | BMI (obese men) (C46) |