Objective: To determine whether important racial, ethnic, or socioeconomic status (SES) health disparities exist in infertility, impaired fecundity, or infertility treatment. Design: Four waves of the National Survey of Family Growth (NSFG) were pooled. Measures were compared across various race/ethnicity, education, and age groups. Participant(s): Data for 31,047 women 15-44 years old from the NSFG were pooled. Intervention(s): Outcomes were compared by whether the women's states of residence had a mandate in place (at least 1 year before the interview) to compel insurers to cover or offer to cover infertility treatment. Main Outcome Measure(s): Infertility status, impaired fecundity, ever having sought infertility treatment. Result(s): Infertility is more common for non-Hispanic black women, non-Hispanic other race women, and Hispanic women than for non-Hispanic white women, and both infertility and impaired fecundity are more common for high school dropouts and high school graduates with no college than for 4-year college graduates, and for older women compared with women 29 and younger. Older women, non-Hispanic white women, and women who are more educated (with at least some college) are more likely to have ever received treatment. No evidence has been found that the racial, ethnic, or education disparities are ameliorated by the health insurance mandates. Conclusion(s):Racial, ethnic, and educational disparities exist in infertility status and treatment, and educational disparities in impaired fecundity. More study of the impact of infertility treatment mandates on these disparities is needed. (Fertil Steril 2006;85:858 -65.

Infertility currently affects over 6 million individuals in the United States. While most health insurance plans nationwide do not cover infertility diagnoses or treatments, to date fifteen states have enacted some form of infertility insurance mandate. In this paper, I use data from the Vital Statistics Detail Natality Data and Census population estimates to examine whether these state-level mandates were successful in increasing fertility rates. Using a difference-in-differences approach, I exploit variation in the enactment of mandates both across states and over time, and identify treatment and control groups that should have been differentially affected by infertility coverage. My results suggest that the mandates significantly increase first birth rates for women over 35, and these results are robust to a number of specification tests.

for sharing data. Wendy Magoronga and Tianyue Zhou provided excellent research assistance. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Wealth accumulation has important implications for the relative well-being of households. This article describes how household wealth in the United States varies by gender and family type. Evidence is found of large differences in observed wealth between single-female-headed households and married couples. Although some of this gap reflects differences in observable characteristics correlated with gender and wealth - such as position in the life cycle, education, and family earnings - controlling for these characteristics reduces but does not eliminate the estimated wealth gap. The wealth holdings of single females in the US, controlling for these same characteristics, are also significantly lower than the wealth holdings of single males. In contrast, observed wealth gaps between genders in a sub-sample of young households disappear when controlling for observable characteristics, suggesting either that in the US these gaps are disappearing for younger households or that these gaps do not emerge until later in life.Wealth, gender, family structure, JEL Codes: D3, J16, J12,

, phone (413) 597-3143; fax (413) 597-4045. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.