1 / 42

Long Distance Travel in GB some insights and forecasts

Long Distance Travel in GB some insights and forecasts. David Quarmby CBE Member and former Chairman, Independent Transport Commission. Transport Planning Society 24 November 2009. Agenda. Agenda. Introduction Patterns of long distance travel Interpreting the drivers of travel

camilla
Download Presentation

Long Distance Travel in GB some insights and forecasts

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Long Distance Travel in GBsome insights and forecasts David Quarmby CBE Member and former Chairman, Independent Transport Commission Transport Planning Society 24 November 2009

  2. Agenda Agenda • Introduction • Patterns of long distance travel • Interpreting the drivers of travel • Looking at scenarios to 2030 • Conclusions

  3. Agenda Introduction • Travel over 50 miles a neglected area of policy • Significant proportion of all CO2 emissions • Lots of modal-specific policy – rail, aviation, strategic road networks…are they linked up? • Unexpected things happening – explosive growth of rail travel; road traffic much less fast, but congestion growing; domestic aviation grows (but less to Heathrow) • ITC commissioned research to explore • What is long distance travel about? What are the patterns? • What are the drivers of travel and what can influence it? • How might this change with different policy scenarios?

  4. Agenda Introduction • ITC commissioned Professor Joyce Dargay, Leeds ITS, to construct 4-mode aggregate demand model, to back-cast known travel trends to 1996 and forecast forward to 2030 • Report completed, to be published with ITC covering report January 2010 • Thanks to Joyce Dargay for her significant piece of research • ITC is very grateful to core sponsors Go-Ahead, Stagecoach and Arriva, and to project sponsors Department for Transport, Rees Jeffreys Road Fund, and Network Rail • Grateful to David Bayliss for chairing the discussion panel, and to Joyce Dargay for joining us to give further insights into the research

  5. Agenda Agenda • Introduction • Patterns of long distance travel • Interpreting the drivers of travel • Looking at scenarios to 2030 • Conclusions

  6. Scope • 4 modes: car rail air coach • 5 journey purposes: business commuting leisure holiday visiting friends and relatives (VFR) • 2 distance bands: 50 to 150 miles 150 miles and greater • Domestic travel by residents of GB within GB • Over 50 miles 1-way • Modelling Aggregate Demand

  7. Data Sources • Principal data sources • National Travel Survey 1995 – 2006 • NTS 2007, 2008 for certain analysis • Transport Statistics Great Britain (TSGB) • Lennon (rail ticketing data) • Long Distance all-mode Travel Survey for this study by ITS • Other sources include • Various DfT publications; HM Treasury; ORR; CAA

  8. Travel by Mode Average annual long distance travel per capita, mean 2002-06, NTS

  9. Travel by Mode Average annual long distance travel per capita, mean 2002-06, NTS

  10. Travel over Time Total long distance travel, 3-year moving average 1995-2006 NTS

  11. Comparison with Total Travel Total passenger miles by mode (1970 – 2007), TSGB*, and total long distance miles (1996 – 2005), NTS * TSGB includes short distance travel and travel by non-households and non-residents

  12. Travel by Purpose Percent of long distance travel by purpose, NTS

  13. Travel by Journey PurposeMode Shares Mode shares of distance travelled by journey purpose, %, mean 2002-2006, NTS

  14. Travel by Journey PurposeMode Shares Mode shares of distance travelled by journey purpose, %, mean 2002-2006, NTS

  15. Travel by Mode & Distance Mode shares of distance travelled by distance band, %, mean 2002-2006, NTS Distance band shares of distance travelled by Mode, %, mean 2002-2006, NTS

  16. Patterns of long distance domestic travel Key points one third of all travel is over 50 miles the car dominates with nearly 80% of travel, rail accounts for 12%, coach and air share 10% car dominates for all journey purposes; rail strong for commuting and VFR; rail and air significant for business; coach significant for holidays and leisure car travel seems to have flatlined in the last few years, with rail continuing to grow 70% of all long distance travel is for holidays, leisure and VFR; business 20%, commuting 10% generally balanced between <150 miles and >150 miles; car journeys tend to be shorter

  17. Agenda Agenda • Introduction • Patterns of long distance travel • Interpreting the drivers of travel • Looking at scenarios to 2030 • Conclusions

  18. The drivers of long distance travel • Elasticities • income elasticity of 0.5 means that a 10% change in income will generate a 5% change in long distance travel • price elasticity of -0.3 means a 10% increase in cost or fares will cause a 3% drop in demand • cross-elasticity – the impact on (eg) rail travel of a particular change in travel times by car • cross-elasticity of 1 of rail travel w.r.t. car travel time means a 5% worsening of car travel times will produce an increase in rail travel of 5%. But don’t forget the effect of relative scale.

  19. The drivers of long distance travel Deriving and interpreting elasticity estimates income – short and long run demographic and geographic factors own and cross elasticities – price and time

  20. The drivers of long distance travel • Income elasticities

  21. The drivers of long distance travel • Income elasticities

  22. The drivers of long distance travel • Income elasticities • car – less than 0.5 Similar across journey purposes, slightly higher for VFR, higher for longer journeys • rail – average under 1 But much higher for business and commuting, similar to car for other journey purposes • coach – unresponsive to income except for longer distance leisure and VFR • air – about 1.5 for all journey purposes - similar to rail for business • as income grows, very different patterns of travel growth

  23. The drivers of long distance travel • Demographic and geographical factors • long distance travel analysed by • household income, gender, age, employment status • Region of residence, size-scale of municipality or rural • number of adults in household, whether children, whether main driver of company car • type of residence, length of residence • Separate models for each of four modes, five purposes and two journey lengths, and the forty in combination

  24. The drivers of long distance travel • Demographic and geographical factors • overall income elasticity 0.42 • longer distance travel more for men than for women • more for those under 60 vs over 60 • more for employed/students than for unemployed/retired • more for those with company cars • declines with longevity at current residence

  25. The drivers of long distance travel • Demographic and geographical factors • those in the South West and East Midlands travel more, and those in the WM and northern regions travel less than average • long distance travel increases as size of municipality decreases, greatest for those in rural areas • the larger the household the less the per capita long distance travel, and least in families with children • greater for those living in detached houses....!

  26. The drivers of long distance travel • Own cost/price and time elasticities – long run • car: cost elasticities -0.3 to -0.8, more for holiday/leisure • rail: around -0.5 for business and commuting; -1.0 to -1.6 for holiday/leisure/VFR • coach: -0.8 to -1.0 • air: -0.4 for commuting; around -1.0 for all other • car: own time elasticities: -1 to > -2 generally; -2.5 for more distant holidays • rail: -0.5 to -0.75 for commuting; -1.5 to 3.0 for all other • coach: -1.3 to -1.75 • air: around -0.5 across all purposes

  27. The drivers of long distance travel • Significant cross elasticities – cost/price and time • for business travel: ~ 0.2 c/e to rail w.r.t. car travel cost • for commuting: ~ 0.2 c/e to rail w.r.t. car travel cost for <150 miles • for holiday: 0.4 to 0.8 c/e to rail w.r.t. car travel cost • for leisure and VFR: 0.2 to 0.4 c/e to rail and coach w.r.t. car travel cost • for business travel: ~1 c/e to rail w.r.t. car travel time • for commuting: ~0.5 c/e to rail and air w.r.t. car travel time • for holiday: ~1.5 c/e to rail and ~0.5 to coach w.r.t. car travel time • for leisure and VFR: 0.7 to 1.0 to rail and coach w.r.t. car travel time; ~1 to coach w.r.t. rail travel time

  28. The drivers of long distance travel So what does this mean for the drivers of long distance travel by each mode? by car: income has a moderate effect, as does the cost of motoring. But worsening of travel times does have a significant impact, especially for longer distance holidays, and does divert demand to rail for business travel, and to rail and (less so) to coach for holidays by rail: income has a major effect on business and commuting, and a strong effect on other journey purposes; fares changes have a moderate effect on business and commuting, but a major effect on holiday/leisure/VFR; changes in travel time affect rail similarly. Switching to other modes is modest or non-existent by coach: travel unaffected by income. Coach fares and travel times have significant effect on demand. Switching to other modes non-existent by air: income has a major effect for all purposes; price elasticity moderate for commuting, high for all other purposes; moderate switching between air (proportionately) and car and rail as their travel times change

  29. Agenda Introduction Patterns of long distance travel Interpreting the drivers of travel Looking at scenarios to 2030 Conclusions Agenda

  30. Agenda Set a base case – with economic, demographic, cost and network assumptions – and project base case to 2030 Identify alternative scenarios Forecast alternative scenarios to 2030 and compare with base case Scenarios to 2030

  31. Input Assumptionsto 2030 • Projections of the population (ONS, GAD) • Population by age and gender • % population 60+ • The number of households • Number of 1-adult households

  32. Input Assumptionsto 2030 • Real GDP forecasts (HMT) – average of independent forecasts • % growth per annum Base case

  33. Input Assumptionsto 2030 • Crude oil price projections (DECC), 2008 US$/bbl Base case Exchange rate: $1.60/ £

  34. Base Case Assumptions

  35. Projections 2030% Change from 2005

  36. Alternative scenarios * % change 2009 to 2030 (base case % change)

  37. Projections 2030% Change from 2005

  38. Projections 2030% Change Base Case

  39. Sensitivity Tests Projections 2030 Billion Person Miles

  40. Agenda Introduction Patterns of long distance travel Interpreting the drivers of travel Looking at scenarios to 2030 Conclusions Agenda

  41. Agenda On reasonable base case assumptions we forecast a 34% increase in long distance travel – 125% by air, 35% by rail, 30% by car and 25% by coach – mostly income driven Universal road charging cuts car demand by 10%, but rail demand is very sensitive (48% growth vs 35% growth) Variations in car fuel efficiency (and cost) affect car travel by + 20%, and a 1% rise in motoring costs especially Air travel very sensitive to APD increases, and fares variations – but still >100% growth for any of the scenarios Coach travel affected by rail pricing and motoring costs lower GDP growth (1.25%) halves the travel growth Conclusions

  42. Long Distance Travel in GBsome insights and forecasts David Quarmby CBE Member and former Chairman, Independent Transport Commission Transport Planning Society 24 November 2009 42

More Related