|
First principles assessment
Profit maximising fare structure
Welfare maximising fare structure
Why introduce a fare structure?
Fare structures are important policy instruments because of their potential
impact upon:
- Efficiency: if a fare structure encourages transfers from car then
it will impact on traffic congestion, possible increase in efficiency
of labour markets due to increased access to jobs, possible reduction
in unproductive travel time.
- Liveable streets: through reduced levels of traffic.
- Protection of the environment: through reduced levels of traffic local
air and noise pollution reduced, reduced pressure on natural resources
such as oil and green space and reduced greenhouse gas emissions.
- Equity and social inclusion: fare structures can impact upon the affordability
of public transport and so access to key goods and services by the socially
excluded and less well off citizens.
- Safety: travelling by public transport is dramatically safer than
travelling by car for the individual that has transferred and also reduces
the number of accidents to vulnerable road users such as walkers and
cyclists.
- Economic growth: if a fare structure encourages transfers from car
then reduce traffic congestion may stimulate economic growth. Improved
access to jobs may also stimulate growth.
- Finance: fare structures can have a significant impact on revenues
and also on costs because they can influence the level of capacity required.
Price elasticities
Demand impacts of a particular fare structure depend upon the price elasticities
in the marketplace. All other things being equal an increase in price
will generally lead to a reduction in demand. The degree of price sensitivity
is known as price elasticity. Demand that is sensitive to price is known
as price elastic whilst demand that is less sensitive to price changes
is known as price inelastic. If a 10% increase in price leads to a 10%
reduction in demand then price elasticity is -1.0. If a 10% price increase
reduces demand by say 3% then price elasticity is -0.3. Finally, if a
given price increase leads to a proportional demand reduction then this
is unit price elastic. The concept of price elasticity is summarised in
Table 2 below:
Table 2: Price Elasticities
| Price change |
Demand response |
Elasticity |
| 10% increase |
20% reduction |
-2.0 (price elastic) |
| 10% increase |
10% reduction |
-1.0 (unit elastic) |
| 10% increase |
3% reduction |
-0.3 (price inelastic) |
Demand impacts depend very much on the design of the particular fare
structure. A fare structure that is designed to maximise operator revenue
will look very different from one which aims to minimise peak road traffic
congestion.
A more detailed treatment of elasticities can be found in the Fare
Levels Instrument, First principles assessment.
The importance of price elasticities
Figure 1 below illustrates the dilemma that a profit maximising transport
operator faces when setting fares. The demand curve (labelled demand)
slopes downward from left to right indicating the diminishing fare that
each subsequent passenger is prepared to pay and so the reducing fare
that is needed in order to increase patronage.
If the operator sets a fare of "c" then it misses out on the revenue
represented by Triangle abc because those passengers would have been prepared
to pay more. On the other hand the operator also misses out on those passengers
that could afford to pay a fare that would deliver a profit (above marginal
cost) but were unwilling to pay a fare of "c", this lost profit is represented
by the Triangle byz.
If a means could be found of obliging those passengers represented by
the ab section of the demand curve to pay a very high fare (covering both
their marginal cost and also contributing to capital costs) whilst allowing
those passengers represented by the section bz to pay a far lower fare,
then both profits and welfare would be increased. The welfare increase
would be as a result of the increased level of public transport supply
that could be supported combined with the fact that even those who can
pay only a small fare would still have access to the system (and therefore
important goods and services).
Distinguishing between different sections of the market in this way is
a crucial function of a fare structure. An obvious example of this is
advance purchase tickets that oblige the passenger to travel on prespecified
trains that are offered by all intercity train companies in the UK. These
stipulations ensure that business users are unlikely to find such tickets
sufficiently flexible and so encourage them to purchase the far more expensive
flexible tickets. With the increasing use of smart cards it is likely
that similar distinctions will begin to appear in an urban context with
fully flexible tickets/season tickets and those which are only valid between
prespecified times.
Figure 1: Supply and Demand of Public Transport
Factors affecting price elasticity
There are a number of factors that will influence the level of the fare
elasticity, these are listed below:
- Fare levels - the higher the current fare the more sensitive passengers
will be to fare changes.
- Size of fare changes - the larger the change in the fare the more
sensitive passengers will be to the fare change.
- Income levels - those on high incomes are less likely to be sensitive
to changes in bus fares, whilst those on low incomes more sensitive.
- Service quality - passengers may be less sensitive to fare changes
if the quality of service is high.
- Competition from other modes - strong competition from other bus operators
and from other modes of transport will make passengers more sensitive
to fare changes. Meaning that passengers with a car available tend to
be more price sensitive.
- Age and sex - Males tend to be more sensitive to fare changes than
females. The elderly and school children are also more sensitive to
fare changes.
- Journey purpose - travellers commuting to work or school tend to be
less sensitive to fare changes, whilst leisure travellers are more sensitive.
- Distance - passengers will be more sensitive to changes in fare if
they are only travelling short distances since walking is always an
option.
- Urban vs. Rural - passengers tend to more sensitive to fare changes
in rural areas compared to passengers in urban areas.
- Area - passengers tend to be less sensitive to fare changes in metropolitan
areas compared with non- metropolitan areas.
- Peak vs. Off Peak - passengers tend to be less sensitive during peak
periods of travel, compared with off-peak periods of travel.
Cross- elasticities and Diversion Rates
Whilst a profit maximising transport operator is likely to have limited
interest in the effect that its fare policies are having on other modes,
a welfare maximising operator will wish to know the source of new patronage.
New trips could have transferred from other public transport modes, walking
and cycling or alternatively represent entirely new travel i.e. generated
trips.
A cross-elasticity represents the impact that a change in a service characteristic
of one mode will have upon demand for other modes. For example, if a 20%
rail fare increase in a given area leads to a 1% increase in car traffic
then the fare cross-elasticity at that particular time between car and
rail would be 0.05.
A diversion rate represents the percentage of new patronage for a given
mode that has come from a specific mode. For example, if a fare reduction
attracts a given number of new passengers, 20% of which are from car,
then it could be said that the diversion rate from car is 20%.
A more complete description and evidence on cross- elasticities is presented
in Konsult
Fare Levels Instrument: first principles assessment.
Whilst a change in fare structure is by no means comparable with a change
in the overall level of fares in terms of impact on other modes, in the
absence of direct evidence on the impact of fare structures, fare cross-elasticities
(or indeed service level elasticities) may provide some
indication of likely diversion rates as a result of fare structure changes.
Profit maximising fare structure
Table 3 below lists the likely policy elements in a profit maximising
fare structure and also provide an explanation for their inclusion.
Table 3: Likely Policy Elements for a Profit Maximising Fare Structure
| Policy element |
Purpose and wider effects |
| Generally high fares especially during the peak |
Maximise revenues and possibly reduce costs by avoiding the need
to invest in the increased capacity. Services less likely to be operating
at capacity because the profit maximising fare level may stifle demand. |
| Very low fares for off-peak leisure travel |
Induce price elastic leisure trips from other modes and generate
entirely new trips. Possibly using off-peak day tickets. |
| High-priced flexible tickets |
To maximise yield from business travellers that need flexibility. |
| Time period passes for regular users |
Regular travellers are more price sensitive and need to be offered
lower fares than one off users. |
| Increasing fares for passengers with no alternative |
Passengers with no car available are captive and are therefore price
inelastic, increased fares would therefore increase revenue. |
| Concessionary fares |
If the group has a price elastic demand - such as children. |
Profit Maximising Fare Structure: Demand Responses
| Table 4: Responses and situations (impact on vehicle trips/mileage)
|
 |
=
Weakest possible response, |
 |
=
strongest possible positive response |
 |
= Weakest
possible negative response, |
 |
= strongest
possible negative response |
 |
= No response
|
Profit Maximising Fare Structure: Short and long run demand responses
| Table 5: Responses and situations (impact on vehicle trips/mileage)
|
|
=
Weakest possible response, |
|
=
strongest possible positive response |
|
= Weakest
possible negative response, |
|
= strongest
possible negative response |
|
= No response
|
Supply impacts
A profit maximising fare structure will aim to make maximum use of existing
capacity whilst avoiding the need to invest in new capacity unless that
can be justified in business terms.
Financing requirements
As noted above, the profit maximising fare structure is effective at
maximising revenue whilst minimising costs and so a movement to such a
structure would reduce required subsidies.
Table 6: Profit Maximising Fare Structure: Expected impact on key
policy objectives
| Objective |
Scale of contribution |
Comment |
| 
|
|
In prioritising the fare yield some capacity may be unused
with some PT users switching to car in the peak in particular |
| 
|
|
Increased road traffic may reduce amenity and increase community
severance |
| 
|
|
By increasing air and noise pollution, and pressures on green
space and environmentally sensitive sites |
| 
|
|
Low income PT users with no car available may be hit by high
fares because they are a captive market with inelastic demand |
|
 |
|
Due to increased traffic levels |
| 
|
|
Increased road traffic congestion may hinder economic growth,
but on the other hand reduced subsidy requirements may reduce the
tax burden and so stimulate growth |
| 
|
|
A profit maximising fare structure can significantly improve
an operator's financial position. |
| = Weakest
possible positive contribution, | | = strongest
possible positive contribution |
| = Weakest
possible negative contribution | | = strongest
possible negative contribution |
| =
No contribution |  | =
Uncertain contribution |
Profit Maximising Fare Structure: Expected impact on problems
| Table 7: Contribution to alleviation of key problems
|
| Problem |
Scale of contribution |
Comment |
| Congestion-related delay |
|
Due to Transfer from Car to PT |
| Congestion-related unreliability |
|
Due to Transfer from Car to PT |
| Community severance |
|
Due to Transfer from Car to PT |
| Visual intrusion |
|
Due to Transfer from Car to PT |
| Lack of amenity |
|
Due to Transfer from Car to PT |
| Global warming |
|
By increasing traffic-related CO2 emissions |
| Local air pollution |
|
By increasing emissions of NOx, particulates and
other local pollutants |
| Noise |
|
By increasing traffic volumes |
| Reduction of green space |
|
By increasing pressure for new road building and city expansion
|
| Damage to environmentally sensitive sites |
|
By reducing traffic volumes |
| Poor accessibility for those without a car and those with mobility
impairments |
|
Passengers without access to a car tend to have a price inelastic
demand which may encourage a profit maximising operator to increase
fares for that group. Without regulation operators may not wish
to encourage increased patronage from the mobility-impaired because
of the potential cost/difficulties in accommodating their needs. |
| Disproportionate disadvantaging of particular social or geographic
groups |
|
Passengers without access to a car tend to have a price inelastic
demand which may encourage a profit maximising operator to increase
fares for that group. Also the removal of cross subsidies between
profit-making and non-profit making routes may reduce services and
increase fares in rural areas. |
| Number, severity and risk of accidents |
|
By increasing traffic volumes. |
| Suppression of the potential for economic activity in the area
|
|
The efficiency of the local road network would be reduced due
to increased congestion. On the other hand the reduced subsidy necessary
may leave authorities in a position to reduce taxes or possibly
stimulate growth by some other means. |
| = Weakest
possible positive contribution, | | = strongest
possible positive contribution |
| = Weakest
possible negative contribution | | = strongest
possible negative contribution |
| =
No contribution | | =
Uncertain contribution |
Expected winners and losers
| Table 8: Winners and losers |
| Group |
Winners / losers |
Comment |
| Large scale freight and commercial traffic |
|
High value journeys – more time spent in congestion the
greater the vehicle utilization – although relatively small
proportion of journey distance in urban conditions. |
| Small businesses |
|
Where these are local and increased car use discourages use
of local amenities. On a wider scale they are likely to disbenefit
from increased congestion. |
| High income car-users |
|
High income associated with high value of time and thus continued
car use for high value journeys. These journeys will disbenefit
from increased traffic congestion. |
| People with a low income |
|
Their accessibility may be reduced due to higher fares. |
| People with poor access to public transport |
|
Removal of cross subsidies whereby high-volume routes subsidise
low-volume routes to ensure maximum network coverage may mean that
those in rural areas are less well served and/or pay higher fares. |
| All existing public transport users |
|
Reduced crowding may benefit some customers that value comfort
highly but for most users this benefit will be outweighed by the
fare increases. |
| People living adjacent to the area targeted |
|
They may disbenefit from increased congestion and more expensive
public transport supply. |
| People making high value, important journeys |
|
Increased road traffic congestion may bring a disbenefit here. |
| The average car user |
|
Will face a disbenefit from increased congestion. |
|
=
weakest possible benefit, |
|
=
strongest benefit |
|
= weakest
possible disbenefet, |
|
= strongest
possible disbenefit |
|
= neither
wins nor loses |
Barriers to implementation
| Table 9: Scale of barriers |
| Barrier |
Scale |
Comment |
| Legal |
|
This will vary greatly according to the context. Under the
Verbund systems in Munich, Zürich, Frankfurt (and others) private
sector operators' fare policies are entirely controlled by the Verbund
administration. In a number of US cities legal challenges have been
mounted under the Environmental Justice legislation in an attempt
to stop public sector operator's changing fare policy (TCRP Report
94). In the UK outside of London however operators have a high level
of freedom.
In the UK If it can be shown that an operator is acting to stifle
competition and is taking advantage of a monopoly position then
it could be investigated by the Monopolies and Mergers Commission
which is part of the Office of Fair Trading www.oft.gov.uk. In reality
it has proved difficult to successfully prosecute in such cases.
Local authorities, with permission from the Secretary of State for
transport, also have the power to implement quality contracts if
it can be shown that this is the only way that they can meet their
LTP objectives. In certain instances this appears to have been used
as a negotiating tool to oblige operators to co-operate with local
authorities.
|
| Finance |
- |
The profit maximising fare structure improves on operator's
financial position so there is no financial barrier. |
| Political |
|
This will vary enormously. A publicly owned operator or private
company that is dependent on government subsidy will be subject
to far more constraints than a wholly commercial operation. |
| Feasibility |
|
The status quo will have an impact on how quickly
an operator can move to a profit maximising fare structure. |
|
=
minimal barrier, |
|
=
most significant barrier |
Welfare maximising fare structure
Table 10 below details the fare policy elements that are likely to form
part of a welfare maximising fare structure and also explains the rationale
for their use in order to maximise welfare.
Table 10: Components of a Welfare Maximising Fare Structure and
Explanation
| Policy element |
Purpose and wider effects |
| Generally lower fares especially during the peak when compared to
a profit maximising structure. |
Maximise patronage so as to reduce externalities associated with
road traffic and also improve accessibility for low income groups. |
| Concessionary fares or even free travel during the interpeak for
particular groups such as the elderly. |
Encourage use by groups that may not be able to afford a full fare
whilst using up spare capacity during the interpeak periods. |
| Simplified fare structure. |
To maximise patronage and particularly Transfer by car users. |
| Time period passes for regular users. |
Regular travellers tend to be more price sensitive and are therefore
offered lower fares than one off users, this would also maximise patronage.
This may also include day passes. |
| Lower fares for low income passengers with no alternative. |
The operator would be unlikely to take advantage of the price inelasticity
of passengers with no car available. |
| Through ticketing arrangements between operators likely. |
In order to maximise passenger convenience and overall patronage
across all operators. |
Welfare Maximising Fare Structure: Demand responses
| Table 11: Responses and situations (impact on vehicle trips/mileage)
|
|
=
Weakest possible response, |
|
=
strongest possible positive response |
|
= Weakest
possible negative response, |
|
= strongest
possible negative response |
|
= No response
|
Welfare Maximising Fare Structure: Short and long run demand responses
| Table 12: Short and long run demand responses |
|
=
Weakest possible response, |
|
=
strongest possible positive response |
|
= Weakest
possible negative response, |
|
= strongest
possible negative response |
|
= No response
|
Supply impacts
A welfare maximising fare structure will aim to maximise patronage so
as to reduce externalities associated with private car use. Lower fares,
in the peak in particular (aiming to maximise accessibility and minimise
traffic congestion) will increase demand and may well necessitate investment
in new capacity, so increasing the supply of public transport. Fares for
disadvantaged groups will often be kept to a minimum - although it can
be argued that such subsidy is inappropriate and that these groups should
be given these funds directly in the form of cash for them to spend as
they see fit.
Financing requirements
A welfare maximising fare structure will lead to a reduction in fare
yield per passenger. Demand will be increased, but with price elasticities
even in the longer term rarely exceeding 1, there will be an overall drop
in revenue. Increased demand, particularly in the peak, may necessitate
increased investment which will put further strain on finances. In order
for a fare reduction to be financially neutral, long-term elasticity must
be greater than 1, as to cover the loss that would be incurred as demand
increased to its new equilibrium.
Welfare Maximising Fare Structure: Expected impact on key policy objectives
Table 13: Expected Impact on Key Policy Objectives
| Objective |
Scale of contribution |
Comment |
|
|
|
In prioritising welfare road congestion will be reduced |
|
|
|
Reduced road traffic may increase amenity and reduce community
severance |
|
|
|
Reduced road traffic will reduce air and noise pollution, and
pressures on green space and environmentally sensitive sites |
|
|
|
Low income PT users will benefit from lower fares |
|
|
|
Due to reduced traffic levels |
|
|
|
Reduced road traffic congestion may improve economic growth,
but on the other hand increased subsidy requirements may increase
the tax burden and so stifle growth |
|
|
|
A welfare maximising fare structure can significantly worsen
an operator's financial position. |
| = Weakest
possible positive contribution, | | = strongest
possible positive contribution |
| = Weakest
possible negative contribution | | = strongest
possible negative contribution |
| =
No contribution | | =
Uncertain contribution |
Welfare Maximising Fare Structure: Expected impact on problems
| Table 14: Contribution to alleviation of key problems
|
| Problem |
Scale of contribution |
Comment |
| Congestion-related delay |
|
Due to Transfer from Car to PT |
| Congestion-related unreliability |
|
Due to Transfer from Car to PT |
| Community severance |
|
Due to Transfer from Car to PT |
| Visual intrusion |
|
Due to Transfer from Car to PT |
| Lack of amenity |
|
Due to Transfer from Car to PT |
| Global warming |
|
By reducing traffic-related CO2 emissions |
| Local air pollution |
|
By reducing emissions of NOx, particulates and other
local pollutants |
| Noise |
|
By reducing traffic volumes |
| Reduction of green space |
|
By reducing pressure for new road building and city expansion
|
| Damage to environmentally sensitive sites |
|
By reducing traffic volumes |
| Poor accessibility for those without a car and those with mobility
impairments |
|
Passengers without access to a car tend to have a price inelastic
demand. A welfare maximising operator will be unlikely to take advantage
of this by increasing fares for that group. A welfare maximising
operator would also be likely to encourage increased patronage from
the mobility-impaired in recognition of their possible dependence
on public transport. |
| Disproportionate disadvantaging of particular social or geographic
groups |
|
Passengers without access to a car tend to have a price inelastic
demand but a welfare maximising operator would be unlikely to take
advantage of this by increasing fares for that group. |
| Number, severity and risk of accidents |
|
By reducing traffic volumes. |
| Suppression of the potential for economic activity in the area
|
|
The efficiency of the local road network would be increased
due to reduced. On the other hand the increased subsidies required
may necessitate increased taxes which may stifle growth. |
| = Weakest
possible positive contribution, | | = strongest
possible positive contribution |
| = Weakest
possible negative contribution | | = strongest
possible negative contribution |
| =
No contribution | | =
Uncertain contribution |
Expected winners and losers
| Table 15: Winners and losers |
| Group |
Winners / losers |
Comment |
| Large scale freight and commercial traffic |
|
High value journeys – less time spent in congestion the
lower the vehicle utilization – although relatively small
proportion of journey distance in urban conditions. |
| Small businesses |
|
Where these are local and reduced car use encourages use of
local amenities. More generally they are likely to benefit from
reduced congestion. |
| High income car-users |
|
High income associated with high value of time and thus continued
car use for high value journeys. These journeys will benefit from
increased traffic congestion. |
| People with a low income |
|
Their accessibility may be increased due to lower fares. |
| People with poor access to public transport |
|
Cross subsidies whereby high-volume routes subsidised low-volume
routes to ensure maximum network coverage and consistency of fares
may mean that those in rural areas are better served and pay lower
fares. |
| All existing public transport users |
|
Increased crowding may benefit some customers that value comfort
highly but for most users this benefit will be outweighed by the
fare increases. |
| People living adjacent to the area targeted |
|
They may benefit from reduced congestion and cheaper public
transport supply. |
| People making high value, important journeys |
|
Reduced road traffic congestion may bring a benefit here to
those travelling by car whilst reduced fares will benefit those
travelling by public transport. |
| The average car user |
|
Will face a benefit from reduced traffic congestion. |
Barriers to implementation
| Table 16: Scale of barriers |
| Barrier |
Scale |
Comment |
| Legal |
|
This will depend very much on the local or national regulatory
framework which will vary greatly. In a century tended market or one
with a public sector operator there would be little constraint on
implementing such a policy. In a deregulated market this would be
more difficult. In the UK outside London for example where the bus
industry is largely deregulated such a fare structure would be very
difficult to impose on private operators. If the major operator is
publicly owned such as is the case with the Tyne & Wear Metro
then it will be far easier but may nonetheless face legal challenges
from competing operators complaining of the use of public funds to
compete unfairly. In a centralised tendering system such as in London
there should be little difficulty in changing fare policy. |
| Finance |
|
The welfare maximising fare structure reduces profitability
significantly and so significant subsidy may well be required. |
| Political |
|
The fare policy itself is likely to be popular, but the taxes
required to support it far less so. |
| Feasibility |
- |
Provided the subsidies are in place there are no
significant constraints on feasibility unless a smart card system
is opted for. |
|
=
minimal barrier, |
|
=
most significant barrier |
Text edited at the Institute for Transport Studies,
University of Leeds, Leeds LS2 9JT
|
