Investigating heterogeneity in the price elasticity of traffic flow in Melbourne: Evidence from traffic volume data

This paper leverages a rich dataset of 1.24 billion traffic flow observations across 36,666 vehicle detectors to estimate the price elasticity of traffic flow with respect to fuel prices in Melbourne, Australia. I find that a 1% increase in fuel prices leads to a 0.0556% decrease in traffic flow across Melbourne, where traffic flow is defined as the number of vehicles passing a vehicle counter per hour. I find significant regional heterogeneity across Melbourne, with evidence of positive own-price elasticities in regions in the centre of the city, and in peak commute times on both weekdays and weekends, which I argue is evidence of a congestion-speed effect. Moreover, regions near the CBD with high incomes tend to be less elastic than regions further away with reduced access to public transport. These findings can be used to determine the optimal tax or charge to internalise the externalities produced by motor vehicles.