- With recent advances in high-resolution satellite imagery and machine vision algorithms, fine-grain geospatial data that maps the distribution of populations across countries are now available: acre-by-acre, worldwide. In this article, we showcase how researchers and policymakers can leverage these novel data to more precisely identify “education deserts” in developing countries – localized areas where families lack physical access to education – than ever before and better diagnose the contextual obstacles preventing universal enrollment for school-aged children. Paired with localized policy expertise, these analyses allow for more refined targeting of educational access initiatives focused on physical factors (such as school construction or transportation infrastructure improvements) and non-physical factors (such as tuition waivers or informational campaigns). We conduct a proof-of-concept analysis in the context of three countries (Tanzania, Kenya, and Rwanda) that have historically struggled with educational access as a demonstration of the utility, viability, and flexibility of our proposed approach.
Castleman, B. L., Bird, K. A., & Kim, B. H. (2019). Pathways to Success: Analyzing Program-Level Heterogeneity in Labor Market Outcomes for a State Community College System. Working paper available upon request.
- Despite a significant body of evidence demonstrating program-level heterogeneity in the wage returns to a community college degree, we currently know little about the extent of program-level heterogeneity in non-wage labor market outcomes for community college graduates. We build on an existing literature by investigating the degree of institution- and program-level heterogeneity across several measures of employability, employment stability, and earnings for graduates of a large state community college system. We further examine whether the relative performance of colleges and programs are sensitive to the specific labor market metric we consider. Our descriptive results indicate substantial changes in the rank ordering of institutions or programs based on the labor market metric we employ. These findings demonstrate the importance of considering–and potentially increasing public sharing of– a broader range of labor market outcomes when assessing community college institutions or program returns.
Works In Progress:
Kim, B. H., & Castleman, B. L. Examining systemic racial and gender bias in teacher recommendation letters for college applications using natural language processing techniques.
Kim, B. H., Bird, K. A., & Castleman, B. L. Crossing the Finish Line but Losing the Race: Socioeconomic Inequalities in Labor Market Trajectories Among Community College Graduates.