Virtually all social science research related to obesity studies a person's body mass index (BMI). Yet there is wide agreement in the medical literature that BMI is seriously flawed because it does not distinguish fat from fat-free mass such as muscle and bone. This paper studies data that include multiple measures of fatness and finds that many important patterns, such as who is classified as obese, group rates of obesity, and correlations of obesity with social science outcomes, are all sensitive to the measure of fatness and obesity used. We show that, relative to percent body fat, BMI misclassifies substantial fractions of individuals as obese or non-obese; in general, BMI is less accurate classifying men than women. Furthermore, when percent body fat instead of BMI is used to define obesity, the gap in obesity between white and African American men increases substantially but the gap in obesity between African American and white women is cut in half. Finally, total body fat is negatively correlated with employment for some groups and fat-free mass is not significantly correlated with employment for any group, a difference that was obscured in previous research that studied BMI. In the long run, social science datasets should include more accurate measures of fatness. In the short run, estimating more accurate measures of fatness using height and weight is not possible except by making unattractive assumptions, but there is also no reason to adhere uncritically to BMI as a measure of fatness. Social science research on obesity would be enriched by greater consideration of alternate specifications of weight and height and more accurate measures of fatness.

No abstract

We estimate the employment effects of federal minimum wage increases using monthly Current Population Survey (CPS) data from 1979 through 1997. We find that the empirical differences in the new minimum wage literature based on CPS data primarily can be traced to alternative methods of controlling for macroeconomic conditions. We argue that the macroeconomic controls commonly included in models where no employment impact is found are inappropriate. We consistently find a significant but modest negative relationship between minimum wage increases and teenage employment using alternative controls or allowing employer responses to the policy to occur with some delay.

Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the U.S. Census Bureau. All results have been reviewed to ensure that no confidential information is disclosed. the referees, for their helpful comments and suggestions on earlier versions of this paper. Abstract Although most research on US income inequality trends is based on public-use March CPS data, a new wave of research using IRS tax return data reports substantially higher levels of inequality and faster growing trends for recent years. We show that these apparently inconsistent estimates are largely reconciled when the income distribution and inequality are defined in the same way. Using internal CPS data for 1967-2006, we show that estimates of top income shares based on internal CPS data for 1967-2006 are similar in many respects to the IRS data-based estimates reported by Piketty and Saez (2003). Our results imply that changes in US income inequality since 1993 are largely driven by changes in the share of the top 1 percent.