The Joint Effect of Restaurant Trans Fat Bans and Menu Labeling Laws on the Prevalence of Hypertension and Coronary Heart Disease 公开
Chen, YuHua (2014)
Published
Abstract
Starting in 2007, several city and state governments have
implemented restaurant related dietary policies to the overall
health outcomes of their constituents. This paper intends to
estimate the average treatment effect of the joint treatment of
trans fat bans and
menu labeling law on both aggregate measure health outcomes
and
individual-level health outcomes. To overcome the problem of policy
overlapping and hidden selection bias, I apply propensity
score
method for the first stage estimation and inverse probability
weighting estimator for average treatment effect on the aggregate
prevalence
of hypertension and coronary heart disease. We find trans fat ban
decreases the prevalence of coronary heart disease by 2 percentage
point.
The average treatment effect of multiple overlapping policies
slightly
decreases the prevalence of coronary heart disease by 1.4
percentage
point. The average treatment effect on the treated of multiple
overlapping policies decreases the prevalence of coronary heart
disease by
1.59 percentage point. I also use individual-level data to estimate
the
effect of Baltimore trans fat ban on the prevalence of
hypertension.
I apply difference-in-differences method and improve the
reliability of
inference by wild bootstrap procedures, I find Baltimore trans fat
ban
decreases the prevalence of hypertension among the elderly by
4.65
percentage point in linear probability model
Table of Contents
List of Tables
1 List of U.S cities with trans fat ban and menu labeling law . .
11
2 Summary Statistics by treatment categories for aggregate data
19
3 Multinomial Logit Model for Propensity Score . . . . . . . . .
22
4 Inverse Probability Weighted Treatment Effect of trans fat
ban
and menu labeling law on prevalence of hypertension and CHD
24
5 Summary Statistics for Individual-level data . . . . . . . . . .
28
6 Regression result of Baltimore trans fat ban . . . . . . . . . .
33
7 Poisson Estimation for count response of health outcome . . .
39
8 Regression result of NYC trans fat ban:Model 1 . . . . . . . .
52
9 Regression result of NYC trans fat ban . . . . . . . . . . . . .
53
About this Master's Thesis
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