Benjamin Ukert

The effect of smoking on obesity: Evidence from a randomized trial

This paper aims to identify the causal effect of smoking on body mass index (BMI) using data from the Lung Health Study, a randomized trial of smoking cessation treatments. Since nicotine is a metabolic stimulant and appetite suppressant, quitting or reducing smoking could lead to weight gain. Using randomized treatment assignment to instrument for smoking, we estimate that quitting smoking leads to an average long-run weight gain of 1.8-1.9 BMI units, or 11-12 pounds at the average height. Semi-parametric models provide evidence of a diminishing marginal effect of smoking on BMI, while subsample regressions show that the impact is largest for younger individuals, those with no college degree, and those in the lowest quartile of baseline BMI.

The Effect of Smoking on Obesity: Evidence from a Randomized Trial

This paper aims to identify the causal effect of smoking on body mass index (BMI) using data from the Lung Health Study, a randomized trial of smoking cessation treatments. Since nicotine is a metabolic stimulant and appetite suppressant, quitting or reducing smoking could lead to weight gain. Using randomized treatment assignment to instrument for smoking, we estimate that quitting smoking leads to an average long- run weight gain of 1.8-1.9 BMI units, or 11-12 pounds at the average height. These results imply that the drop in smoking in recent decades explains 14% of the concurrent rise in obesity. Semi-parametric models provide evidence of a diminishing marginal effect of smoking on BMI, while subsample regressions show that the impact is largest for younger individuals, females, those with no college degree, and those in the lowest quartile of baseline BMI.

Regional differences in the impact of the “Stand Your Ground” law in Florida

In October 2005, Florida relaxed restrictions on the use of lethal force in self-defense with the Florida stand your ground law (SYG). We examined whether and how the impact of the Florida SYG varied based on the demographic and economic conditions of each of its counties. Using data from the Florida Universal Crime Reports on homicides and firearm homicides from 1999 to 2014, we found that the impact differed significantly by county urbanization, unemployment, and pre-law homicide rates. The largest increases in homicide and firearm homicide occurred in proportionally safer, richer, and less ethnically diverse suburban counties. These findings reveal that the law may have had the opposite effect than intended, and more strongly impacted counties considered safe, suburban and economically successful.

The impact of the minimum wage on health

This study evaluates the effect of minimum wage on risky health behaviors, healthcare access, and self-reported health. We use data from the 1993–2015 Behavioral Risk Factor Surveillance System, and employ a difference-in-differences strategy that utilizes time variation in new minimum wage laws across U.S. states. Results suggest that the minimum wage increases the probability of being obese and decreases daily fruit and vegetable intake, but also decreases days with functional limitations while having no impact on healthcare access. Subsample analyses reveal that the increase in weight and decrease in fruit and vegetable intake are driven by the older population, married, and whites. The improvement in self-reported health is especially strong among non-whites, females, and married.

Effects of the Affordable Care Act on Health Care Access and Self-Assessed Health After 3 Years

Using data from the Behavioral Risk Factor Surveillance System, we examine the causal impact of the Affordable Care Act on health-related outcomes after 3 years. We estimate difference-in-difference-in-differences models that exploit variation in treatment intensity from 2 sources: (1) local area prereform uninsured rates from 2013 and (2) state participation in the Medicaid expansion. Including the third postreform year leads to 2 important insights. First, gains in health insurance coverage and access to care from the policy continued to increase in the third year. Second, an improvement in the probability of reporting excellent health emerged in the third year, with the effect being largely driven by the non-Medicaid expansions components of the policy.