Select Committee on Transport, Local Government and the Regions Appendices to the Minutes of Evidence

Supplementary memorandum by Railtrack PLC (TYP 52A)


  This note is in response to the following request by the Committee to Railtrack PLC for clarification arising from Mr Armitt'e oral evidence to the Transport Sub-Committee's inquiry into the Transport 10 Year Plan:

    —  Please provide details of the relative importance of each of the main drivers for growth in rail demand which you have examined (eg GDP, traffic congestion, motoring costs, rail costs)?


  Over the past three years, Railtrack has worked with the Association of Train Operating Companies to produce a new Passenger Demand Forecasting Framework. As part of this work, a computer model was produced, which is now managed under the aegis of the Passenger Demand Forecasting Council, a voluntary association of train operators, the Strategic Rail Authority and the Office of the Rail Regulator. This model uses industry-standard assumptions, based on research into passenger behaviour, about the effect of a number of key external demand drivers on passenger demand. These drivers are:

    —  Economic activity, measured by GDP and employment levels

    —  Road congestion levels

    —  Population changes

    —  Rail fares

    —  Car ownership levels

    —  Motoring costs.

  Railtrack has used this model to develop network-wide forecasts of future deman based on its own views and assumptions on the way in which each of these drivers will change over the next 10 years. As such the forecasts given here represent Railtrack's views alone. Separate models and techniques are used to forecast the effect of changes in the rail service on particular route: these are not discussed here.

  Currently, Railtrack's central forecast is that underlying demand, unconstrained by limitations on network capacity, for rail travel (measured in passenger km) will grown by 37 per cent between 2000-01 and 2010-11. Because of the way the different effects interact within the model, it is not possible simply to disaggregate this figure into the effects of the individual drivers, but by carrying out a series of model runs it is possible to estimate their individual effects (although for the reason stated these individual effects will not sum precisely to 37 per cent).


  The two most significant drivers are economic activity and the increase in road congestion, which together contribute most of the forecast increase in demand, in roughly equal proportions.

  Economic activity is measured by two different variables: Gross Domestic Product, which is assumed to drive demand for non-commuting journeys, and employment levels which are assumed to drive demand for commuting journeys.

  The effect of increasing road congestion is highest for those rail routes which compete with congested roads—principally those to and from, and main arterial routes.

  The forecast increase in populatioln generates a much smaller increase in demand (around one eighth of the total). The effect of increasing car ownership, which principally affects the leisure market, has the effect of depressing demand. Coincidentally, in this scenario, these two factors roughly cancel each other out.

  In the past, the effect of rail fares on demand has been an important one, particularly during the 1980s when pricing was used as a mechanism to regulate demand. However, since privatisation, rail fares have on average risen by roughly the rate of inflation, and we have assumed that, broadly speaking, this trend will continue. On this assumption, the overall effect of rail fare changes on demand will be small: this will depend, however, on the fares policy actually adopted by the industry.

  Railtrack's central scenario assumes no change in motoring costs, with consequently no effect on demand. However, a reduction or increase in motoring costs would give rise to a corresponding reduction or increase in rail demand.


  Three further points should be noted:

    —  The relative contribution of the drivers to the demand forecasts will obviously depend on the levels at which they themselves are forecast to change—the comparisons given herer are based on the inputs used in deriving the 37 per cent figure mentioned above.

    —  The model used disaggregates the passenger rail market both geographically and by market segment, and the relative importance of the drivers will be different for different parts of the market. The analysis presented above is at a national level, although some important differences between market segments are noted.

    —  In the scenario analysed here all the drivers have the effect of increasing demand except for car ownership.

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