Julie K. Smith

Financial hardship and obesity.

There is a substantial correlation between household debt and health. Individuals with less healthy lifestyles are more likely to hold debt, yet there is little evidence as to whether this is merely a correlation or if financial hardship actually causes obesity. In this paper, we use data from the National Longitudinal Survey of Adolescent Health to test whether financial hardship affects body weight. We divide our sample into two groups: men and women, explore two different types of financial hardship: holding credit card debt and having trouble paying bills, and three outcomes: overweight, obese and body mass index (BMI). We use a variety of econometric techniques: Ordinary Least Squares, Propensity Score Matching, Sibling Fixed Effects, and Instrumental Variables to investigate the relationship that exists between financial hardship and body weight. In addition, we conduct several robustness checks. Although our OLS and PSM results indicate a correlation between financial hardship and body weight these results appear to be largely driven by unobservables. Our IV results suggest that there is no causal relationship between credit card debt and overweight or obesity for either men or women. However, we find suggestive evidence that having trouble paying bills may be a cause of obesity for women.

PCE Inflation and Core Inflation

This paper investigates the forecasting accuracy of the trimmed mean inflation rate of the Personal Consumption Expenditure (PCE) deflator. Earlier works have examined the forecasting ability of limited-influence estimators (trimmed means and the weighted median) of the Consumer Price Index but none have compared the weighted median and trimmed mean of the PCE. Also addressed is the systematic bias that appears due to the differences in the means of inflation measures over the sample. This paper supports earlier results that limited-influence estimators provide better forecasts of future inflation than does the popular measure of core inflation, PCE inflation minus food and energy; therefore, these limited-influence estimators are core inflation.

Better Measures of Core Inflation

Recent papers examining the measurement of core inflation, such as the weighted median, have focused on cross-section information in disaggregated inflation data. This paper improves on the literature by introducing a new measure of core inflation that exploits the time-series information in disaggregated inflation data. The new measure is based on a definition of core inflation as the best predictor of future inflation. Exploiting the time-series information in disaggregated or component inflation data produces better forecasts than exploiting cross-section information. Additionally, the new measure comes from jointly estimating the optimal weights instead of imposing weights based on the persistence of the components.

The Effects of Minimum Wages on the Health of Working Teenagers

ABSTRACT This article examines the effect of minimum wage increases on the self-reported health of teenage workers. We use a difference-in-differences estimation strategy and data from the Current Population Survey, and disaggregate the sample by race/ethnicity and gender to uncover the differential effects of changes in the minimum wage on health. We find that white women are more likely to report better health with a minimum wage increase while Hispanic men report worse health.