Erik T. Verhoef, Professor of Spatial Economics

Erik Verhoef is full professor in Spatial Economics and a research fellow at the Tinbergen Institute and the Netherlands Network of Economics (NAKE). As member of the faculty board, Erik is mainly responsible for the research policy of the faculty. 

 

The Economics of Transport

A well-functioning transport system is generally regarded as a necessary condition for sustainable economic growth and welfare in modern societies. Transport allows for physical trade and therewith for spatial specialization in cities, regions, and nations – which is generally believed to be among the key contributors to past growth in prosperity. When taking the form of commuting, transport also allows for a physical separation of the demand for and supply of labour, and therewith for people to choose residential locations with other characteristics, such as space and environmental quality, than those of their work locations. Transport thus allows people, households and firms to undertake different activities at different locations, and the scale at which this is usually done suggests that they enjoy substantial benefits from doing so.

Despite the undeniable advantages of transport, it also poses challenging problems, including traffic congestion, emissions, and traffic safety. Economists usually refer to these problems as the “external costs” of transport: costs that are not reflected properly in market prices, inducing overconsumption of “goods” such as clean air and travel time. The containment of such transport-induced external costs is among the top priorities in transport policies in most modern societies. Another economic motivation for public policy in transport has been the regulation of market power that arises from all sorts of economies of density, as visible in transport nodes such as ports, stations and airports. And third, the supply of transport infrastructure is often a public responsibility.

It is the delicate balance between social costs and benefits of transport, in combination with the complexity of transport behaviour itself – involving, for example, the formation of networks by operators, interacting choices of many individuals within these networks, dynamics of departure time choice and queue formation, etc. – that makes it such a relevant and at the same time challenging field for applied theoretical and empirical economic research.

Describing Behaviour on Transport Markets
To judge whether or not government intervention in transport markets is called for, and if so which form it should take, it is necessary to understand the workings of the markets under consideration. This, in turn, requires a thorough understanding of the behaviour of the relevant actors. Research at the Department of Spatial Economics focuses for example on the spatial (locational) behaviour of firms and households, drawing a link between for instance housing markets and commuting. At a more micro level, to better understand traveller’s behaviour in the shorter run, we study both actual (‘revealed preference’) and hypothetical (‘stated preference’) transport behaviour. This research is for example needed to get empirical estimates of important concepts such as the value of time (what is the social value of travel time reductions?), the value of schedule delay (what is the shadow cost of travelling on less-than-ideal moments to avoid congestion?), and the value of reliability (what would it be worth to society if travel times could be made more predictable and reliable?). (At the same time, we also perform valuation studies of other transport-related social costs, including topics such as the value of a statistical life and the value of fragmentation of landscapes.)

Besides countless individuals, also large operators are active in transport markets. Examples are airlines, airports, and public transport companies. These operators take decisions that have a direct impact on the economic performance of the transport system, such as the choice of network forms, capacities, and fares or other prices. But these operators may have objectives that not always match the public interest, at least not perfectly, so that welfare-maximizing choices cannot be expected from them.  The analysis of the behaviour of these actors often requires application of game-theoretic models closely resembling those used in the Industrial Organization literature.

Characterizing the behaviour of the different actors in a transport market is important but not yet sufficient for predicting the eventual outcome of the market. To do this, one needs, of course, also a description of the supply-side of the market. For transport markets this typically requires the use of a network representation, and a characterization of the (dynamic) performance of such a network. Because this performance in turn depends on the behaviour of these same actors, the identification of a dynamic or even ‘just’ a static network equilibrium can be a daunting task, especially if real-life complications such as unpredictability of travel times are to be taken into account.

Economic Analysis of Transport Policies
Besides the sheer desire to better understand the behaviour on and workings of the transport markets, an important motivation for transport economic research has always been the design and evaluation of transport policies. Policy-related research at the Department of Spatial Economics has focussed on various themes already hinted at above. One is the evaluation of (spatial-) economic impacts of infrastructure. Another one is the analysis of policy instruments, notably pricing and capacity investments, for the containment of externalities in road transport such as congestion and emissions. And a third one is the analysis of policies for markets where market power is important, such as aviation.

In our research we apply a mixture of empirical methods and (network) modelling techniques. An important theme that has received much attention in this work is the economic design and evaluation of so-called ‘second-best’ policies. These are analyses that do not, like textbook models do, assume that a government is operating in a nearly-perfect world with only one problem left to be solved, with a perfect instrument available to address that problem. Instead, these analyses take into account that policies are typically not perfect but are subject to many constraints, while at the same time economic distortions on related markets may cause the transport policy to have indirect effects, positive or negative, that should be taking into account in designing transport policies. Such second-best analyses are usually much more complex than the classical first-best case, and provide great challenges for both analytical and numerical analysis. But there is a reward in these efforts, as they may produce surprising and sometimes counter-intuitive results, which also give important new insights for applied policy making besides their scientific contribution.