This paper studies road safety and accident externalities when insurance companies have market power, and can influence road users' driving behaviour via insurance premiums. We obtain both welfare and profit maximizing marginal conditions for first- and second-best insurance premiums for...

We study road supply by competing firms between a single origin and destination. In previous studies, firms simultaneously set their tolls and capacities while taking the actions of the others as given in a Nash fashion. Then, under some widely used technical assumptions, firms set a...

We analyze a market where firms compete in a conventional and an electronicretail channel. Consumers easily compare prices online, but some incur purchaseuncertainties on the online channel. We investigate the market shares of the two retailchannels and the prices that are charged. We find that...

The traditional bottleneck model for road congestion promotes the implementation of a triangular, fully time varying, charge as the optimal solution for the road congestion externality. However, cognitive and technological barriers put a practical limit to the degree of differentiation real...

In most dynamic traffic congestion models, congestion tolls must vary continuously over time to achieve the full optimum. This is also the case in Vickrey's (1969) 'bottleneck model'. To date, the closest approximations of this ideal in practice have so-called 'step tolls', in which the toll...

When drivers opt for carpooling, road capacity will be freed up, and this will reduce congestion. Therefore, carpooling is interesting for policy makers as a possible solution to congestion. We investigate the effects of carpooling in a dynamic equilibrium model of congestion, which captures...

We study a two-sided market where a platform attracts firms selling differentiated products and buyers interested in those products. In the unique subgame perfect equilibrium of the game, the platform fully internalizes the network externalities present in the market and firms and consumers all...

A novel debate within competition policy and regulation circles is whether autonomous machine learning algorithms may learn to collude on prices. We show that when fims face short-run price commitments, independent Q-learning (a simple but well-established self-learning algorithm) learns to...