Aaron Edlin and Pinar Karaca-Mandic's "Accident Externality from Driving":
We estimate auto accident externalities (more specifically insurance externalities) using panel data on state-average insurance premiums and loss costs. Externalities appear to be substantial in traffic-dense states: in California, for example, we find that the increase in traffic density from a typical additional driver increases total statewide insurance costs of other drivers by $1,725–$3,239 per year, depending on the model. High–traffic density states have large economically and statistically significant externalities in all specifications we check. In contrast, the accident externality per driver in low-traffic states appears quite small. On balance, accident externalities are so large that a correcting Pigouvian tax could raise $66 billion annually in California alone, more than all existing California state taxes during our study period, and over $220 billion per year nationally.
This was an interesting paper and certainly could use more empirical work.
1. I first thought that state level estimates were too coarse but then it sounds logical since insurance premiums seem to differ state by state rather than county by county.
2. This data set seems small enough that I might be curious to find out how the results would change if a multilevel model was used instead. The data is state level from 1987-95 and the authors use a "panel data approach" which I use to mean fixed state and time effects.
3. I also thought they might have computed the costs for all 50 states and then rank order them and present them graphically instead of in a table.