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Institute for Transport StudiesFACULTY OF ENVIRONMENT
PRICE ELASTICITIES OF TRAVEL DEMAND
REVIEW AND META-ANALYSIS
Professor Mark Wardman
MOTIVATIONS
• Why Review?
Price elasticities are important for policy and forecasting
Benchmarking and new insights
Several previous reviews and update needed
• Why Quantify Relationships (Meta-Analysis)?
Conclusions beyond a single study (eg, over time, method)
Exploit results outside public domain
Model can provide elasticity estimates where no evidence exists
Classic literature reviews emphasise means
BACKGROUND: PREVIOUS REVIEWS
Numerous conventional reviews of price elasticities:
TRRL (1980), Goodwin (1992), Oum et al. (1992), Graham and Glaister
(2004), TRL et al. (2004), Wallis (2004), Litman (2010)
Goodwin (1992) - international evidence
50 bus fare elasticities from 21 studies
92 rail fare elasticities from 22 studies
120 car cost elasticities from 13 studies
Oum et al. (1992)
60 international studies of passenger demand
TRL et al. (2004) – local and suburban
33 UK studies and 11 Non UK studies of bus fare elasticities
35 UK and 20 Non UK rail fare elasticities
BACKGROUND: PREVIOUS META-ANALYSES
A few previous meta-analyses covering price elasticities
Hensher (2008) international evidence (price, time, headway)
Meta model 319 observations from 39 studies
Holmgren (2007) range of public domain elasticities
81 for public transport price
Wardman and Shires (2003)
104 UK studies 1968-2002 and 902 PT price elasticities
DATA COVERAGE
• 167 UK studies 1957 to 2010 yielding 1633 price elasticities
Published as: Wardman, M. (2014) Price Elasticities of Surface Travel Demand: A Meta-analysis of UK Evidence. Journal of Transport Economics and Policy, 48 (3), pp.367-384
• Follows on from major meta-analyses of:
1749 UK values of time from 226 studies
Published as: Abrantes, P.A.L. and Wardman, M. (2011) Meta-Analysis of UK Values of Time: An Update. Transportation Research A 45 (1), pp. 1-17
427 UK time elasticities from 69 studies
Published as: Wardman, M. (2012) Review and Meta-Analysis of U.K. Time Elasticities of Travel Demand. Transportation 39 (3), pp. 465-490
• List independent variables
EXPLANATORY VARIABLES
• Multiple observations (elasticities) per study where appropriate
• Key segmenting (e.g. possible influential) variables are:
Type of data and sample size
Mode and cost numeraire
Periodicity (dynamic, static, indeterminate), time period, lag structure
Level of aggregation and model type
Distance, region and type of flow
Journey purpose and/or ticket type
Year
Source
SOME SUMMARY MEASURES
Car: 77 values from 27 studiesRail: 1140 values from 102 studiesBus: 377 values from 60 studiesUnderground: 39 values from 11 studies
Times Series: Short Run 25%, Long Run 24%, Static 27% Choice: RP 4% SP 7%Other 13%
Urban 38% Inter-Urban 50% All 12%
1957-1970 4%1971-1980 21%1981-1990 19%1991-2000 47%2001-2010 9%
SUMMARY ELASTICITIES (I)
CAR RAIL BUS
Time Series/Panel SR -0.30 (0.07) -0.69 (0.02) -0.45 (0.03)
Time Series/Panel LR -0.66 (0.13) -1.11 (0.03) -0.62 (0.04)
Time Series/Panel Static -0.35 (0.18) -0.73 (0.02) -0.36 (0.02)
Cross Sectional -0.61 (0.20) -1.01 (0.14) -0.50 (0.04)
SP Choice -0.20 (0.08) -0.89 (0.07) -0.58 (0.12)
RP Choice -0.13 (0.02) -0.57 (0.09) -0.30 (0.03)
TP -1.23 (0.10) -0.52 (0.06)
Urban -0.10 (0.03) -0.76 (0.04) -0.44 (0.04)
Inter-Urban -0.19 (0.04) -0.88 (0.02) -0.69 (0.11)
All Distances -0.39 (0.06) -0.93 (0.04) -0.72 (0.19)
SUMMARY ELASTICITIES (II)
CAR RAIL BUS
Business -0.13 (0.05) -0.62 (0.06) -0.56 (0.14)
Commute -0.16 (0.04) -0.82 (0.19) -0.35 (0.04)
Peak -0.12 (0.0) -0.34 (0.03)
Leisure -0.13 (0.02) -1.05 (0.12) -0.41 (0.04)
Off Peak -0.55 (0.04)
Season -0.71 (0.03)
1st Class -0.76 (0.06)
Standard Class -0.94 (0.03)
Both 1st and Standard -0.82 (0.02)
Full Fare (Peak) -0.69 (0.06)
Reduced (Off-Peak) -0.97 (0.06)
SUMMARY ELASTICITIES (III)
CAR RAIL BUS
1957-1970 -0.65 (0.39) -0.33 (0.02)
1971-1980 -0.16 (0.04) -0.81 (0.02) -0.43 (0.03)
1981-1990 -0.47 (0.09) -0.91 (0.04) -0.51 (0.04)
1991-2000 -0.25 (0.07) -0.85 (0.02) -0.48 (0.02)
2001-2010 -0.13 (0.02) -1.03 (0.11) -0.53 (0.05)
MODEL FORM
The meta-model takes the form:
jk
q
kjk
p
ji
Zn
ii eX
1
11
1
R2 goodness of fit of 0.64 seems reasonable. No outliers removed. Weighting made little difference 63 ‘study specific’ fixed effects
META ANALYSIS RESULTS (I)
Variable Coeff (t) Effect Variable Coeff (t) Effect
Data Type
Base=Static-Four LR-Quarter(Quarter) n.s. -
Static-Quarter n.s. - LR-Quarter(Annual) n.s. -
Static-Annual 0.388 (7.2) +47.4% LR-Annual 0.544 (9.2) +72.3%
SR-Four -0.144 (2.9) -13.4% Monitor n.s. -
SR-Quarter(Quarter) -0.729 (4.3) -51.8% Cross-Rail 0.483 (2.4) +62.1%
SR-Quarter(Annual) n.s. - Cross-Bus 0.223 (2.0) +25.0%
SR-Annual n.s. - RP Choice n.s. -
LR-Four(Four) 0.345 (6.9) +41.2% SP 0.698 (8.5) +101.0%
LR-Four(Annual) n.s. - TP-Rail 0.793 (8.5) +121.0%
LR-Four(FourAnnual) 0.539 (3.7) +71.4% TP-Bus 0.291 (1.6) +33.8%
META ANALYSIS RESULTS (II)
Variable Coeff ( t) Effect Variable Coeff (t) Effect
Distance Category Area Type
Base=Urban Base=NonUrban
InterUrban-Rail n.s. - UrbanPTE-Rail -0.521 (8.3) -40.6%
InterUrban-Bus 0.228 (1.7) +25.6% UrbanPTE-Bus -0.260 (3.9) -22.9%
InterUrban-CarTrips 0.571 (3.8) +77.0% UrbanNonPTE-Rail n.s. -
InterNonLondon-Rail -0.075 (2.2) -7.2% UrbanNonPTE-Bus -0.206 (2.7) -18.6%
London-Rail -0.466 (3.0) -37.2%
London-Bus n.s. -
META ANALYSIS RESULTS (III)
Variable Coeff (t) Effect Variable Coeff (t) Effect
Mode and Ticket Purpose
Base=Bus Base=Commute-Peak
Car-Trips -1.496 (8.4) -77.6% Business -0.574 (6.4) -43.7%
Car-Km -0.744 (4.9) -52.5% Leisure-OffPeak 0.270 (3.5) +31.0%
Car-FuelCons -0.557 (1.9) -42.7% NonComm n.s. -
Rail-Seasons n.s. - NonEB n.s. -
Rail-First -0.232 (3.2) -20.7% All n.s. -
Rail-Standard n.s. - Car Cost
Rail-Both -0.121 (3.2) -11.4% Base=Fuel
Rail-Full -0.158 (1.8) -14.6% FuelParking 0.154 (1.5) +16.6%
Rail-Reduced 0.128 (2.0) +13.7% Total 0.568 (3.1) +76.5%
UG n.s. -
META ANALYSIS RESULTS (IV)
Variable Coeff (t) Effect Variable Coeff (t) Effect
Price Index Car Ownership
LnPrice-Rail-NonSeason
0.179 (8.0) 0.179 LnCars-LeisKmFuel -1.240 (3.0) -1.240
LnPrice-Bus 0.068 (3.0) 0.068 Elasticity Type
LnPrice-Car n.s. - Base=FullElasticity
LnPrice-UG n.s. - ModeChoice-Leisure -0.276 (1.9) -24.1%
Study Source
Base=Published
Unpublished -0.099 (2.5) -9.4%
IMPLIED RAIL ELASTICITIES
ShortPTE
ShortLondon
ShortOther
InterLondon
InterNonLon
Season SR -0.18 -0.19 -0.31 -0.31 -0.28
Static -0.31 -0.33 -0.52 -0.52 -0.48
LR -0.36 -0.38 -0.61 -0.61 -0.57
PDFH LR -0.40 (-0.60) -0.60 -0.40 (-0.70) -0.60 (-0.75) -0.60 (-0.90)
Non SeasonFirst and Standard
SR -0.37 -0.39 -0.62 -0.62 -0.57
Static -0.63 -0.66 -1.05 -1.05 -0.98
LR -0.73 -0.77 -1.23 -1.23 -1.14
PDFH LR -0.70 (-0.85) -0.80 -0.70 (-1.00) -1.05 -1.20 (-1.00)
First LR -1.10 -1.02
Full LR -0.70 -0.74 -1.19 -1.19 -1.10
Reduced LR -0.94 -0.99 -1.58 -1.58 -1.47
IMPLIED CAR ELASTICITIES
Trips Urban Trips Inter
Km Fuel
Business SR -0.04 -0.07
Static -0.07 -0.12
LR -0.12 -0.21
DfT LR -0.10
CommuteandAll
SR -0.07 -0.12 -0.12 -0.15
Static -0.12 -0.21 -0.21 -0.25
LR -0.21 -0.36 -0.37 -0.45
DfT LR -0.30
Leisure SR -0.08 -0.14
Static -0.13 -0.23
LR -0.23 -0.41
DfT LR -0.40
IMPLIED BUS ELASTICITIES
PTE Urban London & Rural
Inter
Commute SR -0.32 -0.34 -0.42 -
Static -0.55 -0.58 -0.71 -
LR -0.64 -0.68 -0.83 -
Leisure SR -0.42 -0.45 -0.55 -0.69
Static -0.72 -0.76 -0.93 -1.17
LR -0.84 -0.89 -1.09 -1.37
Total LR -0.77 -0.82 -1.00 -
CONCLUSIONS
• Price elasticities critical in transport planning, policy and pricing
• Largest meta-analysis of price elasticities ever undertaken
• Summarises a number of key relationships
• Considerable practical value
• Methodological insights
• How do price elasticity meta-analysis findings fit with:
time elasticity meta-analysis evidence?
value of time meta-analysis evidence?
• Would be nice to extend to other countries!