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This chapter presents a Bayesian analysis of the endogenous treatment model with misclassified treatment participation. Our estimation procedure utilizes a combination of data augmentation, Gibbs sampling, and Metropolis–Hastings to obtain estimates of the misclassification probabilities and the treatment effect. Simulations demonstrate that the proposed Bayesian estimator accurately estimates the treatment effect in light of misclassification and endogeneity.

In March 2010, President Obama signed into law the most broad and sweeping reform of health care in U.S. history. This was done at a time when aggregate medical expenses are significantly higher than they have ever been:

Questions have arisen as to whether the school environment is currently a contributing factor to the increase in childhood obesity, and whether changes in school policies could help curb the increase. In this chapter, we discuss key aspects of the literature on the role of the school food environment, and the role of the school activity environment in effecting the caloric intake and expenditure of children. We also simulate the effect of a range of reasonable changes in weekly minutes spent being active in school, and changes in weekly calories consumed in school.

Over the past three decades, the U.S. economy experienced a sharp increase in the labor-force participation of women, causing a similar increase in the demand for non-parental child care. Concurrent with these developments has been a dramatic rise in the prevalence of childhood obesity, prompting the question as to what extent the increase in child-care utilization is responsible for the growth in obesity. This chapter examines the impact of various child-care arrangements on school-age children's weight outcomes using panel data from the Early Childhood Longitudinal Study, Kindergarten Cohort (ECLS-K). An advantage of the ECLS-K for our purposes is that it tracks children's child-care arrangements between Kindergarten and the 5th grade. Our fixed-effects' results suggest that non-parental child-care arrangements are not strongly associated with children's weight outcomes. Our findings are robust to numerous sensitivity and subgroup analyses.

Universal helmet laws (UHLs) are widely believed to be effective in reducing motorcycle fatalities. In this chapter, we further investigate the effectiveness of such policies by focusing on their long-term impact as well as their effect on motorcycle use. Using state-level longitudinal data from 1975 to 2005, we estimate how the adoption and repeal of UHLs influence motorcycle safety. Our results confirm earlier findings that adoption of UHLs prevents fatalities, whereas repeals lead to higher fatality rates. We provide evidence that UHLs operate as intended, decreasing fatalities mainly by improving safety rather than by reducing motorcycle riding. Finally, using dynamic specifications, we show that the long-term effects of both adoption and repeal persist in the years beyond the policy change.

This chapter examines whether or not the introduction of a new $20 family premium in Kentucky's Children's Health Insurance Program (CHIP) program in late 2003 had a differential impact on the enrollment duration of children in different demographic groups, with a special focus on any potential differences by race or ethnicity. A competing risk hazard model is estimated in order to differentiate between children exiting CHIP via a transfer to Medicaid and children who exited public coverage completely. We find that non-white children are generally more likely to exit than white children. This general white/non-white difference increases immediately following the introduction of the $20 premium