Long-term demand effects in public transport

Abstract

Demand elasticities are of vital importance to everyone who is involved in public transport planning and management. Being a measure of the demand effects of changes in for example fares or service levels, the elasticities provide planners with an efficient planning tool. There is increasing evidence that the short run demand response is only a fraction of the total (i.e. long run) demand effects. In the short run most passengers have few alternatives to the services they currently depend on. In the longer run, passengers are able to respond more fully to such changes by e.g. changing location of job or dwelling, or changing their car ownership status. Several studies indicate, therefore, that long run effects are in the region of 1.5 to 3 times as large as the effect within a year. There is also some evidence suggesting that the effects of positive and negative changes may not be symmetrical. This effect may be more pronounced in the long term as people adapt to the changes and change behaviour. However, planners are not always aware of this important distinction between short-run and long-run effects. The most widely used elasticity measure is the short run elasticity. This fact means that there is a risk that the negative effects of fare increases or service withdrawals are substantially underestimated in current planning practice. A better understanding of the dynamics of public transport demand will give rise to better evaluation of proposed public transport measures, improved precision of forecasts, better long term planning; in sum improved planning and policymaking. The paper investigates and documents the growing literature on long-run demand effects in public transport. It comprises two parts. The first part looks at the methodological issues related to the concept of long run elasticities, and explains different estimation methods and practices. The second part summarises important recent empirical findings in the literature. Finally, the paper draws conclusions for policy making and for public transport planning in general. For the covering abstract please see ITRD E135207.

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