The corresponding rates in the nationally representative data from our CCP-NSC sample (described in our first post) are respectively 22 percent and 21 percent for the two-year and four-year public school students. We find that 37 percent of AA students, and 21 percent of BA students were ever delinquent on their student loan by age 30. We will refer to the former group of students as AA students and to the latter group of students as BA students. The charts shown below are split into two panels: the upper panel represents results for students who enter CUNY for an associate (AA) degree, while the lower panel depicts results for students who enter CUNY for a bachelors (BA) degree. Once again, we utilize multivariate regression analysis and present bar charts for the regression coefficients of interest these show the correlations between demographics, educational outcomes, and debt delinquencies, controlling for factors such as immigration and visa status, type of high school attended, year of entry to CUNY, and whether a student has a disability, is economically disadvantaged, or is an English language learner. (See the previous post for more detail on this topic.) Were these disparities in debt behavior by gender, race, and education level associated with differences in financial stress, as captured by delinquencies? This post focuses on this question.Īs in our previous post, we draw on a novel merger of individual-level demographic and education data from CUNY and consumer debt data from the New York Fed/Equifax Consumer Credit Panel, resulting in an anonymous data set covering more than 84,000 students who entered CUNY as first-time freshmen between 19. In the first post, we examined how the propensity to take out household debt and loan amounts varied among students by race, gender, and education level, finding notable differences across all of these dimensions.
#SUBPRIME MORTGAGE DEFAULTS BY DEMOGRAPHICS SERIES#
This post is the second in a three-part series exploring racial, gender, and educational differences in household debt outcomes. Ruchi Avtar, Rajashri Chakrabarti, and Kasey Chatterji-Len
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