TY  - JOUR
AB  - Geographic proximity to college is a widely used instrument for estimating returns to postsecondary education. Most applications rely on geodesic ("crow-flies") distance, which is easy to calculate but a poor proxy for actual travel costs when terrain, water, or congestion intervene. We show that replacing geodesic distance with driving distance or driving time substantially strengthens instrument performance. Using administrative data on Maryland public high school graduates linked to postsecondary records, we find that driving time raises the first- stage F-statistic for years of postsecondary education from 13 to 266, well above the F > 100 threshold recommended by Lee et al. (2022) for reliable 2SLS inference. To facilitate adoption, we introduce drivingtime, an R package that queries the Google Maps Distance Matrix API to generate driving distances and travel times for researcher-defined origin-destination pairs.
AU  - Delaney, Taylor
AU  - Marcotte, Dave E.
PY  - 2026
ST  - Improvements in Using Distance to Predict College Enrollment
TI  - Improvements in Using Distance to Predict College Enrollment
UR  - http://www.edworkingpapers.com/ai26-1608
ER  -