Presentation by Professor Mark Wardman delivered to an International Transport Workshop: Railway Transport Economics organised by Argentine Railways, June 2014.

1. Institute for Transport Studies
FACULTY OF ENVIRONMENT
GROWING AND UNDERSTANDING
PASSENGER RAIL DEMAND
What Can be Learnt from
Recent British Experience?
Professor Mark Wardman

2. OBJECTIVES OF
PRESENTATION
• THEME OF TALK:
Are there lessons to be learnt from British railway experience?
• FOCUS OF TALK:
Commercial: evolution of passenger demand and revenue
• SCOPE OF TALK:
Suburban and inter-urban rail but not tram/metro
• STRUCTURE OF TALK:
Why is British Railway Experience Relevant?
What is happening in Britain and how do we understand it?
What might Argentine Railways learn from Britain?

3. BACKGROUND: THE CURRENT
ORGANISATION OF UK RAIL
SINCE 1995 …….
•Separate infrastructure provider (Privatised Railtrack and
then Public Sector Network Rail)
•19 franchised train operating companies, 5 open access train
operators, 12 parent companies
•Franchises were 7 years, now minimum 10 up to 22 years
•Office of Rail Regulation - Economic and Safety Regulation
•Department for Transport – specifies, awards and monitors
franchises
•3 rolling stock leasing companies

4. LEARNING FROM
INTERNATIONAL EXPERIENCE
• France
Extensive and pioneering high speed network
RER excellent suburban network
BUT outside main lines and Paris: poor service, financially unviable, cost
inefficient – SNCF 1937 model
• Japan
Very dense and efficient network, and impressive high speed services
Privatised 1980s – vertical integration.
Highest rail mode share worldwide (31% of pass km)
• Spain
Impressive high speed network
Starved of investment elsewhere and serious financial problems

5. LEARNING FROM
INTERNATIONAL EXPERIENCE
• Germany
Efficient
Strong patronage growth
Commercial objectives in long distance, competitive tendered
local/regional
Gradual liberalisation
• Switzerland
Regular interval timetable with excellent connectivity
Very reliable services
Highest rail shares in Europe (18% against EU27 of 6%)
Strong and sustained demand growth

6. LEARNING FROM
INTERNATIONAL EXPERIENCE
• Great Britain
High fares (Only 42 per cent of passengers are satisfied with the value
for money for the price of their ticket)
Only 109 kilometres of high speed (300 kph) line
A 150 year old rail network near to capacity
Poor integration between modes (and sometimes between rail services)
Rail share 7% (much less outside London)
Only 1 metro system and only 5 cities with a light rail system (route!)
• So what can possibly be learnt from Britain?

7. BRITISH EXPERIENCE
Wide range of experience and practice that impacts on revenue
•Privatised but regulated
Price controls on monopoly infrastructure provider and operators
Competition for the market (19 franchised operators)
On-track competition (5 open access operators and where franchises
overlap)
•Commercial objectives since 1980s
Long distance flows operating profit in 1980s
Incentives contribute to strong revenue growth
•Long history of structured economic/financial appraisal
Passenger Demand Forecasting Handbook (since 1986)
London Underground New Victoria Line Appraisal (1963)
Cambrian Coast (Rural Railway) Closure Appraisal (1969)

8. BRITISH EXPERIENCE
• Extensive Data on Rail Demand
Ticket sales 2000+ to 2000+ stations by four weekly period, numerous
ticket types and covering many years
In 1980s, largest data set outside the Pentagon!
Management information not just accountancy system
• Supported Extensive Analysis of Travel Demand (see below)
• Appreciated other data sources (see below)
• Unprecedented demand growth (see below)
• Track record of innovation and initiatives (see below)
• Some impressive recent performance statistics (see below)

9. BRITISH EXPERIENCE
• Evidence of Supporting Extensive Research Evidence Base
• Major review studies/meta analyses have revealed:
UK prices elasticities (Wardman JTEP 2014)
167 UK studies and 1633 elasticities
Rail ticket sales data: 66 (40%) studies and 931 (57%) elasticities
UK journey time elasticities (Wardman Transportation 2012)
377 time elasticities from 69 UK studies
Rail ticket sales data: 44 (64%) studies and 263 (70%) elasticities
UK valuations of time (Abrantes and Wardman, Trans Res A 2011)
1619 valuations from 203 UK studies
303 (19%) from 56 (28%) studies commissioned by Railway Industry
UK valuations of reliability (Wardman and Batley, Transportation 2014)
11 studies and 40 late time values, 6 studies and 36 late time elasticities

10. COVERAGE OF RAIL
FUNDED RESEARCH IN UK
In addition to key factors of fare, journey time and economic activity,
many research studies covering a wide range of issues (E.G):
•Car parking provision
•Security at stations
•Crowding (seated in crowded trains and standing up)
•On-train and off-train information provision
•Revenue protection
•Station improvements and staffing
•Different types of seating layout
•Recovery time
•Cleanliness
•Rolling stock type, design and comfort
•On-board facilities (e.g. catering, wi-fi, toilets, information)
•And many more ………..

12. COUNTRIES WITH LARGEST
DEMAND GROWTH (%)
2010/1990 2010/2000
Sweden 72 38
Great Britain 70 47
Belgium 59 35
Switzerland 51 52
Spain 47 13
Netherlands 42 7
France 40 27
Germany 39 13

13. RATIO OF DEMAND
2011 TO 2007
Germany 0
France -1.5
Netherlands –.4
Spain -3.1
Swiss+3.3
Sweden+1
UK -4.3
Belgium 0.5

14. EU EUROPEAN RAIL
COMPARISON STUDY 2013
“We made clear in our 5 year plan published in January that we are under
no illusion about the challenges that both we, and the passengers who use
the railway, face on a daily basis, and the need to keep improving from the
low base to which Britain's railway had sunk in the 1990s.
We continue to work with other railways so that we can all learn from best
practice in our businesses and we welcome efforts by the Commission to
provide improved consistency and transparency of data.”
David Higgins, chief executive, Network Rail
•Passenger satisfaction evidence for a mix of changes since 1990s and
current relative performance
•14 attributes – for example: satisfaction, productivity, mode share,
reliability, safety, demand growth …..
•UK top in 4, second in 2, third in two and fourth in 3
•UK top passenger satisfaction overall of 25 EU railways
(Germany 7th
, France 10th
, Italy 23rd
)

15. BRITISH EXPERIENCE
• Track record of price/marketing innovation and initiatives
1968 selective prices manual moved from distance to market based pricing
1970s – ‘two part pricing’ – Railcards purchased to allow discount fares
1980s – ‘Saver Fares’ for long distance market.
– Extensive promotional offers (2 for 1, add-ons, multi-buys, joint
promotions with retailers)
1990s – Yield Management
2000s – fares regulation
– more fares innovation (discount tickets now 40% revenue)
– More promotional offers (Direct marketing, reward schemes,
add-ons, trial offers)
• Higher (lower) prices in inelastic (elastic) markets.
• Use spare capacity in off-peak
• Minimise abstraction from higher revenue

16. AN EXAMPLE:
MANCHESTER TO LONDON
Price differentiation in UK far exceeds anywhere else
•First Class Any Train Peak Single £230
•Standard Class Any Train Peak Single £160
•Standard Class Any Train Off-Peak Single £78
•First Class Advance (Specific Train) £30 (Off-Peak) - £210 (Peak)
•Standard Class Advance (Specific Train) £20 (Off-Peak) - £140
(Peak)
£1 ≈ 14 ARS

17. BRITISH EXPERIENCE
• Rail Passenger Demand Doubled since 1995 privatisation
• Peak Rail Arrivals London Commuters 31% increase since
1996 (over ½ million passengers per day)
• National rail fares increased on average by 89 per cent
between 1997 and 2012, which corresponds to a 22 per cent
increase in real terms.
• 6 per cent real terms reduction in motoring costs over period,
while bus fares increased in real terms by 28 per cent.
• Government support £ per head (per pass km)
Britain 85 (0.10)
Sweden 244 (0.21)
Switzerland 226 (0.09)
Germany 141 (0.14)

18. PRIVATISATION EFFECT
ON DEMAND
• Privatisation/franchising has stimulated demand by:
Innovations and initiatives
Newer rolling stock
More frequent services
Better performance
Low priced fares on some routes (demand at expense of revenue)
• But other factors at work
Structural change/regionalisation
Mobile technology
Car congestion
Car use, company cars, student debt, inner city living
• Considerable uncertainty as to what has caused recent demand increases
• Empirical evidence on privatisation effect on demand is limited

19. WHAT WAS HAPPENING AT
TIME OF PRIVATISATION?
Actual and Forecast Growth 1990-1998
Flows GDP
Growth
Forecast
Growth
Actual
Growth
To London 100-200 miles 11.8% 6.3% 59.4%
To London > 200 miles 10.5% 6.3% 53.6%
Non London <20 miles 11.6% 5.6% 11.3%
Non London 20-100 miles 12.0% 10.7% 18.2%
Non London 101-200 miles 12.8% 10.7% 33.9%
Non London > 200 miles 12.6% 10.7% 28.4%
SE to London >20 miles 20.9% 5.0% 23.1%

20. WHAT EXPLAINS WHAT
HAPPENING AT PRIVATISATION
Estimated Determinants of Demand (Multipliers)
London Non London South East
GDP 1.301 (1) 1.196 (1) 1.149 (1)
Car Time 1.043 (4) 1.031 (5) 1.067 (3)
Fuel Cost 1.045 (3) 1.056 (2) 1.049 (5)
Population 1.038 (5) 1.022 (6) 1.055 (4)
Car Ownership 0.975 (6) 0.951 (3) 0.972 (6)
Post 1995 1.119 (2) 1.033 (4) 1.092 (2)
Total 1.606 1.307 1.440

21. PASSENGER DEMAND
FORECASTING HANDBOOK
• Unique amongst railway administrations worldwide
• PDFH came about in 1986:
Provide consistent and solid basis for investment appraisal across BR
Supporting well founded investment proposals at Dept for Transport
• Intention to update regularly with evidence base
First Edition June 1986
Second Edition 1989
Third Edition 1997
Fourth Edition 2002
Fifth Edition 2009
• Demise predicted post privatisation (or 25 sets of values)
• Was the worst kept secret in the nationalised rail industry
• Now widespread access through a ‘research club’

22. 22
PDFH: ELASTICITY DRIVEN
FORECASTING APPROACH
Employment instead for seasons/commuting trips
GDP is per capita

23. 23
FARES FORECASTING
Suppose we have a system of tickets (could be
modes)
………… plus other terms
This is the Department for Transport’s STRATEGIC
FARES MODEL used in regulating fares

24. CUSTOMISING THE
CROSS ELASTICITIES
fij is cross elasticity of demand for mode i (rail) with respect to some
variable (say cost) on mode j (bus)
Vj/Vi denotes the relative shares of j (bus) and i (rail)
δji is the ‘diversion factor’ – proportion of change in mode j (bus) who
divert to mode i (rail) when mode j (bus) changes
• Demonstrates variability of cross elasticities
• PDFH uses to customise mode and ticket type cross elasticities
Also used conditional elasticities (for example, for reduce tickets is:)
• fr_Cond = fr1 + frf + frr + fra

25. TIMETABLE RELATED
SERVICE QUALITY (GJT)
V =kGJTg
GJT = J + S + I
•J is the station-to-station journey time
•S is the service interval penalty
•I is the sum of the interchange penalties for
any interchanges required.
Implicit elasticities to the three components are:
g is GJT elasticity, NOT time elasticity

26. 26
RELIABILITY AND
OTHER VARIABLES
L is average lateness of trains in ‘base’ or ‘new’ situation
wr is the weighting to convert one minute of lateness into
equivalent journey time
Analogous approach for:
• Crowding (Seated in crowded train or standing)
• Access/Egress Time
• New Rolling Stock
• On-board facilities
So overall PDFH covers all the main variables of interest

27. HOW IS PDFH APPLIED
IN PRACTICE?
The practical applications here covered are:
•Business Planning – Trend Growth
•Franchise Bidding – External Factors in Action
•Reliability Incentives – Schedule 8
•Government’s Medium Term Strategic Objectives – High
Level Output Specification
But there are numerous other applications, e.g.
•Fares regulation
•Crowding appraisal
•Revenue sharing among operators

28. LONGER TERM FORECASTING
FORECAST DEMAND INCREASES FROM GDP GROWTH (NON SEASONS)
10 years 20 years
1.5% 2.0% 2.5% 1.5% 2.0% 2.5%
Long Distance to London 33% 46% 60% 77% 113% 156%
Long from London 14% 20% 25% 31% 43% 56%
SE to London 19% 27% 34% 43% 61% 81%
Non London Core Long 19% 27% 34% 43% 61% 81%
Non London Non Core Long 13% 18% 23% 29% 40% 52%
Non London Short 13% 18% 23% 29% 40% 52%

29. LONGER TERM FORECASTING
• Value of a train company essentially driven by GDP and
employment growth
• 1% per annum employment growth
13% season ticket growth after 10 years, 30% after 20 years
• 1% fuel price increases per annum
5% demand increase after 10 years, 10% after 20 years
• 1% congestion increases per annum
Up to 7% demand increase after 10 years, up to 15% after 20 years
• 1% bus fare increases per annum
Around 2% demand increase after 10 years, 4% after 20 years

30. FRANCHISE BIDDING
• The Department for Transport specifies the core franchise
Minimum service level, fares regulated (RPI + 1%), performance targets
• It then has built a ‘comparator model’ – PDFH compliant
• Uses this model to develop a ‘shadow bid’ to evaluate bids
• Franchise bidder can offer more or bid more
• Department evaluates bidders and selects preferred

31. HIGH LEVEL OUTPUT
SPECIFICATION
• The High Level Output Specification (HLOS) sets out:
what the Government wants to be achieved by railway activities (during the
period 2014 to 2019).
the funds that are available to secure delivery
• It is a statutory requirement of the Railways Act 2005.
• Does not specify the detail of how these strategic outputs met
• In period 2014/15 – 2018/19
train operators will pay £1.5 billion to operate franchises
Network Rail (Infrastructure provider) will get £18.3 billion grant (for new
schemes and maintaining the existing infrastructure)

32. HIGH LEVEL OUTPUT
SPECIFICATION
• For the period 2014-2019, the government declared four
priorities
‘Electrified Spine’
Increase capacity and improve inter-urban journey times
Facilitate commuting into major urban areas
Improves links to airports (and ports for freight)
• It specified the major investment projects it wishes to see
• It specified new targets on reliability, capacity
• It expected continued improvements in safety, passenger
satisfaction and value for money

33. HOW DOES THE GOVERNMENT
WORK OUT WHAT IT CAN AFFORD?
• PDFH provides the basis for evaluation
• But it is a forecasting equation not a modelling tool
• And it doesn’t cover ‘supply side’
NETWORK MODELLING FRAMEWORK
• PDFH application tool with supply/cost side
• 566 x 566 origin-destination zone pairs for whole of GB
• Full fare tickets, reduced fare tickets, season tickets
• Used to test options for High Level Output Specifications

34. NETWORK MODELLING
FRAMEWORK
• For each Origin-Destination movement, specify changes in
exogenous factors, fares and train services (GJT)
• Calculate changes to base demand
• Assign the base demand to the network
• Determine changes in crowding and performance
• Iterate the demand element due to changes in crowding and
performance until convergence
• Determine operator costs
• Appraise – are schemes worth it?

35. RELIABILITY INCENTIVES:
SCHEDULE 8 (I)
• Aim
to incentivise Train Operators and Network Rail to maintain and improve
their operational performance
• Designed to
compensate operators for the financial impact of poor performance
attributable to Network Rail and other train operators
align financial incentives - so improve operations where cost is less than
benefits to operators. Operators consider impacts on other operators
provide appropriate signals for investment decision-making by all
concerned
• Revised based on PDFH evidence in 2000, 2005 and 2013
• All based on detailed information on train performance

36. RELIABILITY INCENTIVES:
SCHEDULE 8 (II)

37. THE FINANCIAL CONSEQUENCES
OF SCHEDULE 8
• Calculations using MRE done on flow basis.
• 2012-13 financial year Network Rail had to pay £136m to
train operators as a result of delays caused
• This is 20% of the annual profits
• Schemes is incentivising improvements in reliability
performance (see earlier graph)

38. SO WHAT IS TRANSFERABLE
TO ARGENTINE RAILWAYS?
These conclusions based on commercial issues
•PDFH is unique worldwide and is worth copying!
•Create evidence base for Argentina - do not reinvent the wheel!
Use Evidence from Elsewhere
Use Experience from Elsewhere
•Avoid mistakes from UK
Ensure adequate funding of research – particularly matching/collaborative
Avoid parochial viewpoint
Take a long-term strategic view and plan
•Critical is to identify a Champion – person or organisation

39. SO WHAT IS TRANSFERABLE
TO ARGENTINE RAILWAYS?
• Needs data to support evidence base
Record or measure the amount of travel (use new
technology)
Monitor the behavioural effects of improvements
Collect survey based evidence on travel patterns
Undertake market research on passenger preferences and
attitudes
Observe peoples’ choices
• Need to build skill base

40. CONCLUSIONS
• Sustainable railway needs to be more financially secure
• Need to grow the market (as well as more cost efficient)
• Identify marketing (price, product, promotion, place) that
Have been successful elsewhere in growing the rail market
Are relevant to the Argentine context
• Give train operators the freedom, encouragement and
incentives to grow the rail market based on best relevant
international practice
• Need to monitor and understand the rail market
• Need effective means of appraisal