Project Background

A growing body of work has demonstrated that increases in the generosity of cash and in-kind benefits received by low-income women from economic security policies (ESPs) are associated with improved birth outcomes. Most low-income families do not use ESPs in isolation, but rather "package" them to make ends meet. While the effects of Supplemental Nutrition Assistance Program, the Earned Income Tax Credit, and the minimum wage have been studied extensively, there have been few studies of Unemployment Insurance and no identified studies of the combined effects of these four ESPs. This study will examine how individual ESPs and ESP combinations compare to one another in terms of the size of their effects on birth weight and timing. Additionally, this study will be the first to determine the relative contribution of four potential mediators explaining the link between ESP generosity and birth outcomes (i.e., healthcare access, food insecurity, psychological distress, and prenatal health behaviors). Lastly, this study will identify whether the effects of ESP generosity are moderated by poverty level, race, marital status, and education. Low-income but working households account for most of the poverty in the US and their ranks are likely to grow in the wake of the Great Recession and the COVID-19 pandemic. This suggests a pressing need for information on which policies generate the greatest returns, how they influence birth outcomes, and for whom they are most effective. As such, this research will contribute significantly to scientific and policy efforts to improve birth outcomes among low-income women.

Student Role

The research project described above is supported by 1R01HD107077-01A1 from the National Institute of Child Health and Human Development. The student's primary responsibilities would center around:

(1) Reviewing literature: searching peer-reviewed journals for relevant articles and summarizing their findings;

(2) digitizing data and verifying data: finding publicly available "raw" data on the internet and/or downloading data and/or converting data into Excel format and checking data for any errors and/or inconsistencies;

(3) Generating descriptive statistics: calculating tables and graphs displaying how the data is distributed. The student would also be involved in professional development activities aimed at fostering a better sense of the scientific process and the researcher's role within it (see below.)

Student Learning Outcomes and Benefits

As a long-time instructor of social statistics, I have delivered curriculum on the subject to thousands of students, many of whom express finding the content more accessible, useful, and interesting than they ever imagined. Bringing my classroom approach and a host of high-quality internet training resources (e.g., introductions to popular statistical software programs) to the SPUR mentorship, the student will develop a strong sense of statistical literacy and facility with the basics of statistical analysis. These skills are highly valued in the labor market and there is an increasing demand for graduates with statistical literacy, if not abilities. Local, regional, national, and global industries seek a workforce able to interpret data and place a premium on workers with the skills to analyze data independently. Moreover, the student will be included in at least one presentation and/or publication as part of their project involvement, providing compelling evidence of their research abilities to prospective employers. Lastly, the professional development activities described above will provide a solid foundation to flexibly support whatever academic and career goals students may set beyond the SPUR experience.