Traffic congestion is a major problem in large cities worldwide. This project uses high-frequency data from the Los Angeles metropolitan area combined with an instrument that varies spatially and temporally to estimate the causal impact of an additional vehicle mile traveled on travel times. Specifically, the research team exploits the network structure of the Los Angeles highway system and uses crashes on close alternative routes as exogenous shocks to traffic demand. To do so, the team relies on Google Maps to determine the ideal route and alternatives for over 19,000 real-world commutes. The researchers estimate that at peak times an additional trip reduces speed by, on average, 0.22%. They find the optimal toll at peak times is 33 cents per mile, with the toll being lower, even zero, off-peak. The researchers show how this toll varies over space and time, as well as report on its distributional effects. This toll would more than double highway speeds during peak times and only requires reducing vehicle miles traveled (VMT) at the peak by 10%. The resulting social welfare gains are over two billion dollars per year.
