We estimate the relationship between fuel prices and driving speeds on the German Autobahn. The speed price elasticities are higher on sections without a speed limit (−0.047) than on those with a limit (−0.033), thus underlining the distortionary effect of speed limits on previously estimated elasticities. We also find higher elasticities when drivers are alone on the road, for high prices, and slower drivers. Based on the undistorted speed price elasticities, we estimate the short-run fuel demand elasticity and the revealed value of time (20.71 Euro/h; 83% of gross wage), hence providing valuable input for policymakers and infrastructure planning.

This paper analyzes how street space should be allocated across cars, buses, bicycles, and parking in order to maximize economic efficiency. Accordingly, we set up a nested logit model reflecting user heterogeneity, cross-congestion effects between transport modes, and relevant transport demand elasticities. Simulations are conducted for Berlin, Germany and New York City, USA. We find that re-allocating street space from cars to buses and especially bicycles improves efficiency. Effect magnitudes and the extent of optimal re-allocations vary between cities. We also shed light on the channels through which re-allocations impact on efficiency.