Roads, Crashes, and Substances: A Geocoded Atlas of Western US Traffic Fatalities

Abstract

We construct and document a novel integrated dataset combining fatal traffic crashes in Western US states from the Fatality Analysis Reporting System (FARS) with OpenStreetMap road network attributes and marijuana legalization policy timing. The resulting dataset of approximately 70,000 crashes (of which roughly 90% have valid geocoding) enables unprecedented granularity in studying the geography of impaired driving. We document three key patterns: (1) among fatal crashes with any drug finding reported in 2018–2019, the share with THC detected is approximately 20% in legalized states versus approximately 10% in comparison states (illegal during our study period); (2) THC detection rates show visible discontinuities at several state borders in 2018–2019, with patterns varying across border pairs (motivating spatial RDD designs); (3) alcohol involvement exhibits a secular decline from approximately 40% in the early 2000s to under 30% in recent years. Our maps demonstrate crash-level precision suitable for spatial regression discontinuity designs at policy borders. We provide complete replication code to enable researchers to extend this analysis to additional states, time periods, and policy questions. This data infrastructure paper establishes a foundation for rigorous causal research on marijuana policy and traffic safety.