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Recent Evidence on Mass Transit Demand

Recent Evidence on Mass Transit Demand. Ian Savage Northwestern University. Update of a classic report.

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Recent Evidence on Mass Transit Demand

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  1. Recent Evidence on Mass Transit Demand Ian Savage Northwestern University

  2. Update of a classic report . . . • F. Vernon Webster and Phillip H. Bly (editors), The Demand for Public Transport: Report of an International Collaborative Study of the Factors Affecting Public Transport (a.k.a “The Black Book”), Crowthorne, UK: Transport and Road Research Laboratory, 1980

  3. The new report . . . • Richard Balcombe (editor), The Demand for Public Transport: A Practical Guide, Report TRL593, Crowthorne, UK: TRL Limited, 2004 • Literature review and summary of evidence • Practical handbook

  4. Look at responsiveness to . . . • Fares • Travel time • Other quality attributes

  5. Fares

  6. Main changes in 20 years . . . • New research has shown significant difference between short-term (immediately after fare change) and long-term (several years later) fare elasticities • Evidence that fare elasticity has become less inelastic in recent decades

  7. Definition of price elasticity . . . • ep = % change in demand divided by % change in price • Usually negative • 0>ep>-1 = “inelastic” - fare increase leads to increased farebox revenue • -1>ep>-infinity = “elastic” - fare increase leads to decreased farebox revenue

  8. Change from Simpson-Curtin -0.3 . .

  9. Why has it changed . . . • Increased car ownership and changes in work locations have made alternatives to transit more competitive • Now understand that the full effect of price change is only apparent over the long run as people only adjust mode choice when “life cycle event” occurs (marriage, kids, new house, divorce, new job etc)

  10. If bus has price elasticity = -1 in long run . . . • Increased fares may increase revenue in short run, but not over the long run • Not the case for mass transit rail • As short-run elasticities have changed from -0.3 to -0.4, fare increases generate smaller increases in revenue than they used to

  11. Peak versus off-peak elasticities . . .

  12. Suggests time-of-day pricing . . . • Price increases in the peak produce largest increases in revenue with loss of the least amount of riders • Off-peak fare discounts are the most effective at increasing ridership • Reverse of most transit pricing?

  13. Travel Time

  14. Overall service elasticity . . . • eq = % change in demand divided by % change in vehicle-miles • Bus short-run elasticity of +0.4, long-run elasticity of +0.7 • More sensitive in evenings and Sundays

  15. Increased service comprises . . . • More routes - shorter walk time to and from stops • More buses on each route - shorter average waiting time • Also less crowding & faster boarding - faster average journey speeds

  16. Valuation of time . . . • Maybe more productive to think of valuing travel time in dollars so as to make it comparable with fare paid • Concept of “generalized cost” of travel = fare + valuation of time + valuation of other attributes (positive and negative)

  17. Travel time composed of . . . • Access time (at origin and destination) • Waiting time • In-vehicle time (IVT) • Interchange penalty (if applicable)

  18. Not all time is created equal . . . • Minute of access time valued at 1.4 to 2.0 times minute of in-vehicle time (IVT) • Waiting time valued at 1.6 IVT at bus stops and 1.2 IVT at rail stations • Bus interchange penalty valued equivalent to 20 minutes of IVT

  19. Implications . . . • Reducing average wait time by a minute is more effective at generating demand than increasing operating speeds • Variability in waiting time (late running) disliked. Waiting time beyond posted arrival time valued at 2 to 3 times “normal” wait time • Eliminating the need to interchange will be very attractive

  20. Valuing time . . . • Many studies in past twenty years • Related to person’s income and journey purpose • Approximate values per minute of IVT • Access and wait time will be valued higher

  21. Value of IVT in ¢/minute . . .

  22. Concept of a travel time budget . . . • Concept of a daily budget of about 60 minutes in travel • Increase in travel speed compensated for by longer trip (eg. relocate residence further from work place)

  23. Other Quality Attributes

  24. Valuing quality . . . • Typically have used “stated preference” (SP) techniques developed in recent years • Quality of waiting environment valued at up to equivalent of 2 minutes of IVT • Provision of Real Time Information valued at up to equivalent of 3 minutes of IVT

  25. Balancing Fares and Service Levels

  26. Literature . . . • First theoretical work in the 1970s • Empirical applications in Britain and Australia in early 1980s • Ian Savage and August Schupp, "Evaluating Transit Subsidies in Chicago," Journal of Public Transportation, Volume 1:2 (Winter 1997), pages 93-117. • Data for CTA bus and rail 1994

  27. Basic idea . . . • For a given budget constraint (level of subsidy), transit companies can choose many combinations of fares and service levels. - high level of service and fares - low levels of service and fares • Only one of these combinations maximizes the number of riders

  28. Mathematically . . . • Demand = f (price, time taken) • Time taken is inversely related to service levels • Total Farebox revenue = P*f(P,VM-1) • Total Cost = c(VM) • For subsidy of $B P*f(P,VM-1) + B = c(VM)

  29. Societal benefits of extra subsidy. . . • From reduced fares - financial saving - reduced road congestion - but more crowded buses and trains • From increased service - waiting time reduced - less crowded buses and trains - reduced road congestion?

  30. Benefits per $1 of subsidy . .

  31. Weekday off-peak bus service. . . • Reduced service costs society: $1.11 • Transit agency gains: $1 • Fare cut costs agency: $1 • Social benefit of price reduction: $1.77 • Net improvement to society of $0.66 at no cost to transit agency

  32. Move from position 1 to 3 . . .

  33. Savage and Schupp found . . . • Maximize social benefit by cutting service by 30% and using cash saved to reduce fares by 60% • Particular benefits from trimming peak service levels and reducing fares in off-peak

  34. Contact Information: • ipsavage@northwestern.edu • (847) 491-8241 • www.econ.northwestern.edu Look under “faculty” tab to link to my personal web site

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