Human Capital Formation during Childhood and Adolescence: Evidence from School Quality and Postsecondary Success in California
*Names in bold indicate Presenter
As for when school quality matters, this paper is the first paper to compare the effect of school quality on long-run outcomes across elementary, middle, and high school. This is possible because I follow students from 2nd to 11th grade, while prior research has only focused on a single school level. I find that high school quality has the largest effect on postsecondary enrollment, while elementary and middle school quality have the largest effect on college readiness. Thus the different school levels contribute to different aspects of human capital formation, which is consistent with the literature showing that the timing of human capital investments is an important determinant of their effectiveness. Early education provides the skills necessary to succeed later in college, while high school quality likely has a large impact on postsecondary enrollment due to its proximity to the college decision process.
As for whom school quality matters, this paper is the first to allow for within-school heterogeneity by socioeconomic status in how much schools increase the postsecondary enrollment of their students. I find that while schools increase the test scores of their low- and high-income students by similar amounts, they increase the postsecondary enrollment of their high-income students by much more than they do for their low-income students. Low-income students attend college at lower rates than their high-income peers, and I find that schools may contribute to the persistent achievement gap in postsecondary enrollment.
I measure school quality by applying the value added with drift methodology, as in Chetty, Friedman, and Rockoff (2014), to schools. Value added methodologies control for selection on observables in order to account for the fact that students do not randomly sort to schools, and they measure how much schools improve the performance of their students. The drift methodology, which allows value added to change from year to year, is particularly suited to the school quality setting, as schools experience faculty and staff turnover that could lead to changes in quality from year to year. I estimate both how school value added on standardized test scores translates to postsecondary success as well as estimate a school's total value added on postsecondary enrollment directly. Studies comparing value added estimates to school quality estimates obtained using random assignment of students to schools via school admission lotteries show that while there is some small bias in value added estimates, they are policy relevant because they rank order schools correctly.