Supplementary memorandum by Railtrack
PLC (TYP 52A)
10 YEAR PLAN
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
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 roadsprincipally
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
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 changethe 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