6 research outputs found
Within-School Heterogeneity in Quality: Do Schools Provide Equal Value Added to All Students?
Low-socioeconomic status (SES), minority, and male students perform worse than their high-SES, non-minority, and female peers on standardized tests. This paper investigates how within-school differences in school quality contribute to these educational achievement gaps by SES, ethnicity, and sex. Using individual-level data on the universe of public-school students in California, I estimate school quality using a value added methodology that accounts for the fact that students sort to schools on observable characteristics. I run three separate analyses, in which I allow each school to provide a distinct value added to their low-/high-SES, minority/non-minority, and male/female students. I find that there is within-school heterogeneity in value added by SES, ethnicity, and sex, as on average schools provide less value added to their low-SES, minority, and male students. Thus within-school heterogeneity in quality is one factor that contributes to differential outcomes for disadvantaged students
Within-School Heterogeneity in Quality: Do Schools Provide Equal Value Added to All Students?
Low-socioeconomic status (SES), minority, and male students perform worse than their high-SES, non-minority, and female peers on standardized tests. This paper investigates how within-school differences in school quality contribute to these educational achievement gaps by SES, ethnicity, and sex. Using individual-level data on the universe of public-school students in California, I estimate school quality using a value added methodology that accounts for the fact that students sort to schools on observable characteristics. I run three separate analyses, in which I allow each school to provide a distinct value added to their low-/high-SES, minority/non-minority, and male/female students. I find that there is within-school heterogeneity in value added by SES, ethnicity, and sex, as on average schools provide less value added to their low-SES, minority, and male students. Thus within-school heterogeneity in quality is one factor that contributes to differential outcomes for disadvantaged students
Human-Capital Formation During Childhood and Adolescence: Evidence from School Quality and Postsecondary Success in California
This paper investigates the role of school quality in human-capital formation. Specifically, I investigate how the timing of school quality differentially affects long-run outcomes. Using individual-level data on the universe of public-school students in California, I estimate elementary-, middle-, and high-school quality using a value-added methodology that accounts for the fact that students sort to schools on observable characteristics. I then determine the impact of school quality on future K-12 and postsecondary outcomes. I find that high-school quality has the largest impact on postsecondary enrollment, while elementary- and middle-school quality play a larger role in college readiness. In other words, early human-capital investments are important for future postsecondary success, but the unique timing of the college decision process allows for later human-capital investments to also play a significant role
Human-Capital Formation During Childhood and Adolescence: Evidence from School Quality and Postsecondary Success in California
This paper investigates the role of school quality in human-capital formation. Specifically, I investigate how the timing of school quality differentially affects long-run outcomes. Using individual-level data on the universe of public-school students in California, I estimate elementary-, middle-, and high-school quality using a value-added methodology that accounts for the fact that students sort to schools on observable characteristics. I then determine the impact of school quality on future K-12 and postsecondary outcomes. I find that high-school quality has the largest impact on postsecondary enrollment, while elementary- and middle-school quality play a larger role in college readiness. In other words, early human-capital investments are important for future postsecondary success, but the unique timing of the college decision process allows for later human-capital investments to also play a significant role
Right Here Right Now (RHRN) pilot study: testing a method of near-real-time data collection on the social determinants of health
Background: Informing policy and practice with up-to-date evidence on the social determinants of health is an ongoing challenge. One limitation of traditional approaches is the time-lag between identification of a policy or practice need and availability of results. The Right Here Right Now (RHRN) study piloted a near-real-time data-collection process to investigate whether this gap could be bridged. Methods: A website was developed to facilitate the issue of questions, data capture and presentation of findings. Respondents were recruited using two distinct methods – a clustered random probability sample, and a quota sample from street stalls. Weekly four-part questions were issued by email, Short Messaging Service (SMS or text) or post. Quantitative data were descriptively summarised, qualitative data thematically analysed, and a summary report circulated two weeks after each question was issued. The pilot spanned 26 weeks. Results: It proved possible to recruit and retain a panel of respondents providing quantitative and qualitative data on a range of issues. The samples were subject to similar recruitment and response biases as more traditional data-collection approaches. Participants valued the potential to influence change, and stakeholders were enthusiastic about the findings generated, despite reservations about the lack of sample representativeness. Stakeholders acknowledged that decision-making processes are not flexible enough to respond to weekly evidence. Conclusion: RHRN produced a process for collecting near-real-time data for policy-relevant topics, although obtaining and maintaining representative samples was problematic. Adaptations were identified to inform a more sustainable model of near-real-time data collection and dissemination in the future