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White Rose Research Online

http://eprints.whiterose.ac.uk/

Institute of Transport Studies

University of Leeds

This is an author produced version of a paper published in Transport Policy. This

paper has been peer-reviewed but does not include final publisher proofcorrections or journal pagination.

White Rose Research Online URL for this paper:

http://eprints.whiterose.ac.uk/2034/ Published paper Paulley, N.; Balcombe, R.; Mackett, R.; Titheridge, H.; Preston, J.M.; Wardman, M.R.; Shires, J.D.; White, P. (2006) The demand for public transport: The effects of fares, quality of service, income and car ownership. Transport Policy, 13(4), pp.295-306.

White Rose Consortium ePrints Repository eprints@whiterose.ac.uk

THE DEMAND FOR PUBLIC TRANSPORT: THE EFFECTS OF FARES,

QUALITY OF SERVICE, INCOME AND CAR OWNERSHIP

Neil Paulley Richard Balcombe TRL, Crowthorne House, Nine Mile Ride, Wokingham, Berkshire, RG40 3GA Roger Mackett Helena Titheridge Centre for Transport Studies, University College London, UK John Preston Transport Studies Unit, University of Oxford, UK Mark Wardman Jeremy Shires Institute for Transport Studies, University of Leeds, UK Peter White Transport Studies Group, University of Westminster, UK Abstract This paper reports on key findings from a collaborative study whose objective was to produce an up-to-date guidance manual on the factors affecting the demand for public transport for use by public transportoperators and planning authorities, and for academics and other researchers. Whilst a wide range of factors was examined in the study, the paper concentrates on the findings regarding the influence of fares, quality of service and income and car ownership. The results are a distillation and synthesis of identified published and unpublished information on the factors affecting public transport demand. The context is principally that of urban surface transport in Great Britain, but extensive use was made in the study of international sources and examples.

1 Introduction

This paper reports on the key findings of a collaborative study undertaken by the Universities of Leeds, Oxford and Westminster, University College London and TRL Limited (Balcombe et al, 2004). The objective of the study was to produce an up-todate guidance manual for use by public transport operators and planning authorities, and for academics and other researchers. The context of the study was principally that of urban surface transport in Great Britain, but extensive use was made of international sources and examples.

While a wide range of factors was examined in the study, the findings relating to fares, quality of service and car ownership are the most significant and this paper concentrates on these. However, as Balcombe et al (2004) make clear, in practice the factors cannot be treated either in isolation from each other or in isolation from many other direct and indirect influences on public transport demand. The main study also considered new transport modes such as guided busways, the relationship between land use and public transport supply and demand, and the impacts of transport policies generally on public transport. It also looked at the influence of developments in transport and technology over the past two decades, such as innovations in pricing, changes in vehicle size, environmental controls on emissions, and developments in ticketing and information provision facilitated by advances in computing.

1.1 Background

In 1980 the then Transport and Road Research Laboratory, now the Transport Research Laboratory (TRL), published a collaborative report: The Demand for Public Transport (Webster and Bly, 1980). This report, which became widely known as “The Black Book”, identified many factors which influence demand and where possible, given the limitations of the data that were available for analysis, quantified their effects. The Black Book subsequently proved to be of great value to public transport operators and transport planners and policy makers. However, in the following 20 years there has been a great deal of change in the organisation of the passenger transport industry, the legislative framework under which it operates, in technology, in the incomes, life-styles and aspirations of the travelling public, in car ownership levels, and in the attitudes of policy makers. While these changes have not invalidated the general conclusions of the Black Book, they will have reduced the relevance to modern conditions of much of the quantitative analysis. The new collaborative study, of which the result in this paper are a part, was therefore set up to take account of another 20 years’ worth of public transport information, and more recent advances in transport research techniques. The overall objectives of the study

were therefore to:

undertake analysis and research by using primary and secondary data sources on the factors influencing the demand for public transport;





produce quantitative indications of how these factors influence the demand for public transport;

provide accessible information on such factors for key stakeholders such as public transport operators and central and local government.

produce a document that assists in identifying cost-effective schemes for improving services.

1.2 The scope of the paper

The results presented in this paper are a distillation and synthesis of identified published and unpublished evidence on the influencing factors drawn from three key

areas:

fundamental principles relating to transport demand;

evidence from research carried out since publication of the 1980 report.

empirical results for a range of modes.

Where possible, this paper looks at changes in response parameters since the 1980 study.

The data for the study mainly came from existing studies and literature identified through searches for relevant literature in publication databases, material supplied by public transport operators and local authorities and contacts with researchers engaged in analysis in the field. The information was collected, assessed for relevance and, as far as was possible, quality, and an analysis and synthesis made of implications of the overall body of evidence; a meta-analysis of fares elasticities was also conducted. In assessing the evidence it was recognised that fares elasticities, for instance, can be derived in a number of ways, for example: time trends, stated and revealed preference surveys, before-and-after studies, time series analysis, cross sectional analysis, and logit modelling. All of these approaches have their advantages and disadvantages, depending on the context in which the original research was conducted. The various methodological approaches were noted during the information gathering exercise to ensure that the outcomes did not contain unwanted bias.

Most findings reviewed relate to the urban and regional market, with some references to rural areas. The inter-city, long-distance market as such is not covered, and hence ‘long’ distances refer to about 30 kilometres, as in the orginal study of 1980.

–  –  –

2.1 Summary of overall findings Fares are fundamental to the operation of public transport since they form a major source of income to operators. In general, if fares are increased, patronage will decrease. Whether revenue increases or decreases as a result of a fare increase depends on the functional relationship between fares and patronage as represented by the demand curve. Usually this is expressed through the concept of ‘elasticity’. In its simplest form the value of the fares elasticity is the ratio of the proportional change in patronage to the proportional change in fares. It has a negative value when, as is usually the case, fares and patronage are inversely related: an increase in fares leads to a decrease in patronage and vice versa. If the value of the elasticity is in the range zero to -1, then a fares increase will lead to increased revenue. If the value exceeds -1, then a fare increase will lead to a decrease in revenue 1.

Fare elasticities are dynamic, varying over time for a considerable period following fare changes. Therefore it is increasingly common for analysts to distinguish between short-run, long-run and sometimes medium-run elasticity values. There are various definitions of short-, medium- and long-run, but most authors take short-run to be 1 or 2 years, and long-run to be around 12 to 15 (although sometimes as many as 20) years, while medium run is usually around 5 to 7 years.

As well as considering the direct effects of a change in fares, it is often important to consider the effects of fare changes on other modes. The usual method to take into account the effect that other modes have on the demand for a particular mode of public transport is to use cross-elasticities, estimating the demand elasticity for a competing mode with respect to the change in the given mode.

Fare elasticity varies significantly depending not only on the mode, and the time period over which it is being examined, but also on the specific circumstances in which a mode is operating. In the study, elasticity values from many sources were examined to provide an up-to-date overview of fares elasticities and the effects of various factors on the values. The principal results of this analysis are shown in Table 1 and Figure 1. It can be seen that, broadly speaking, bus fare elasticity averages around -0.4 in the short run, -0.56 in the medium run and -1.0 in the long run; metro To avoid confusion in comparisons of elasticities, many of which are negative, the terms “increase” and “decrease” will always in this paper refer to the change in the magnitude (the numerical part) of the elasticity. Thus an elasticity which changes from -0.5 to -0.7 is said to have increased fare elasticities average around -0.3 in the short run and -0.6 in the long run, and local suburban rail around -0.6 in the short run. There is evidence for this in Dargay and Hanly (1999) and Gilbert and Jalilian (1991).

These results appear to indicate a significant change from those reported by Webster and Bly (1980), which were based on international aggregate measures of fares elasticity for all journey purposes and passenger types across all trip lengths and fares.

This analysis led to the conclusion that overall fares elasticities are low, so that increases in fare levels will almost always lead to increases in revenue. The analysis resulted in the then accepted ‘standard’ public transport fares elasticity value of -0.3.

Given the dominance of before-and-after studies in the 1980 report, it is likely this value is what would now be called a short-run elasticity. In the current work the short run elasticity has been found to be about -0.4.

Two of the main reasons for this difference are as follows. Firstly, given that fare elasticity is different for different journey purposes, there may have been a shift in the proportions of journeys of different types for which people are using public transport (for example, more leisure travel). Secondly, for the same journey purpose the elasticity may actually have changed. This could be due a variety of factors, some of which will interact with each other: one of these is increased rate of market turnover, insofar as potential new users may have different perceptions of using public transport. Other factors include: rising incomes and car ownership and the varying quality of public transport service over the last 20 years. Interestingly suburban rail short run fare elasticity has changed very little, remaining at about -0.5.

The 1980 report did not cover medium or long run elasticities at all. Therefore the likely value of medium run bus fare elasticity of around -0.56 cannot be compared with earlier estimates.

The realisation that long-term elasticities can exceed -1 has serious implications for the public transport industry. While the immediate effect of a fare rise might be a temporary increase in revenue, the long-term effect is likely to be a decrease, although if future cash flows are discounted, operators may benefit from fare increases.

Nevertheless, attempts to counter falling revenue with fare increases alone will eventually fail. Reversal of negative trends in public transport patronage requires service improvements, and possibly fare reductions.

The relatively wide ranges of elasticity values about the means shown in Table 1 and Figure 1 reflect variation in methods of estimation, as well as variation between studies in a number of other factors influencing demand and elasticity. A few of the more significant disaggregations are considered below.

–  –  –

Figure 1: Summary of mean values and ranges of fare elasticities Public transport UK&outside SR

2.2 Effect of types of fare change Fare elasticities may be affected by the magnitude of the fare change. In general, greater fare increases produce higher values of elasticity than lower increases. There is evidence of this from modelling of rail fares in south-east England by Mackett and Bird (1989). The differences are greatest for long-run elasticities. Fare elasticity is also affected by the current level of the fare relative to people’s income. This can be illustrated by the results for London buses. When fares were particularly low, from October 1981 to March 1982, the elasticity was around -0.30 to -0.33, but at the higher relative fare levels in 1983, it was over -0.40 (Collins, 1982). Elasticity values have also been found to increase with fare levels for short distance ( 32km) rail journeys outside London (Association of Train Operating Companies, 2002).

The response to a fare increase may not be equal and opposite to the response to a fare decrease; that is, they may not be symmetrical. The evidence is however limited.



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