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Institute for Transport Studies FACULTY 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 studies Rail: 1140 values from 102 studies Bus: 377 values from 60 studies Underground: 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) -1.23 (0.10) -0.52 (0.06) TP 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 Leisure -0.12 (0.0) -0.13 (0.02) -0.34 (0.03) -1.05 (0.12) Off Peak -0.41 (0.04) -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 META ANALYSIS RESULTS (I) Variable Coeff (t) Effect Variable Coeff (t) Effect Data Type Base=Static-Four Static-Quarter Static-Annual n.s LR-Quarter(Quarter) n.s - - LR-Quarter(Annual) n.s - 0.544 (9.2) +72.3% n.s - 0.388 (7.2) +47.4% LR-Annual SR-Four -0.144 (2.9) -13.4% Monitor 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) LR-Four(Annual) LR-Four(FourAnnual) 0.345 (6.9) +41.2% SP n.s - TP-Rail 0.539 (3.7) +71.4% TP-Bus 0.698 (8.5) +101.0% 0.793 (8.5) +121.0% 0.291 (1.6) +33.8% META ANALYSIS RESULTS (II) Variable Coeff ( t) Effect Variable Distance Category Area Type Base=Urban Base=NonUrban Coeff (t) Effect 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 Mode and Ticket Purpose Base=Bus Base=Commute-Peak Car-Trips -1.496 (8.4) -77.6% Business Car-Km -0.744 (4.9) -52.5% Leisure-OffPeak Car-FuelCons -0.557 (1.9) -42.7% NonComm Rail-Seasons n.s Rail-First Rail-Standard -0.232 (3.2) n.s - NonEB -20.7% All Coeff (t) Effect -0.574 (6.4) -43.7% 0.270 (3.5) +31.0% n.s - n.s - 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% +13.7% Total 0.568 (3.1) +76.5% Rail-Reduced UG 0.128 (2.0) n.s - META ANALYSIS RESULTS (IV) Coeff (t) Effect -1.240 (3.0) -1.240 Variable Coeff (t) Effect Variable Price Index Car Ownership LnPrice-Rail-NonSeason 0.179 (8.0) 0.179 LnCars-LeisKmFuel LnPrice-Bus 0.068 (3.0) 0.068 Elasticity Type LnPrice-Car n.s - Base=FullElasticity LnPrice-UG n.s - ModeChoice-Leisure Study Source Base=Published Unpublished -0.099 (2.5) -9.4% -0.276 (1.9) -24.1% IMPLIED RAIL ELASTICITIES Season Short PTE Short London Short Other Inter London Inter NonLon 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 -0.40 (-0.60) -0.60 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 -0.70 (-0.85) -0.80 -0.70 (-1.00) -1.05 -1.20 (-1.00) -1.10 -1.02 PDFH LR Non Season First and Standard PDFH LR -0.40 (-0.70) -0.60 (-0.75) -0.60 (-0.90) First LR 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 Business SR Static LR DfT LR Commute SR and Static All LR DfT LR Leisure SR Static LR DfT LR -0.04 -0.07 -0.12 Trips Inter -0.07 -0.12 -0.21 -0.07 -0.12 -0.21 -0.12 -0.21 -0.36 -0.08 -0.13 -0.23 -0.14 -0.23 -0.41 Km Fuel -0.10 -0.12 -0.21 -0.37 -0.30 -0.15 -0.25 -0.45 -0.40 IMPLIED BUS ELASTICITIES Commute Leisure Total PTE Urban Inter -0.34 London & Rural -0.42 SR -0.32 Static -0.55 -0.58 -0.71 - LR -0.64 -0.68 -0.83 - 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 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 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! [...]... -0.40 IMPLIED BUS ELASTICITIES Commute Leisure Total PTE Urban Inter -0.34 London & Rural -0.42 SR -0.32 Static -0.55 -0.58 -0.71 - LR -0.64 -0.68 -0.83 - 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 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... 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! ... Total 0.568 (3.1) +76.5% Rail-Reduced UG 0.128 (2.0) n.s - META ANALYSIS RESULTS (IV) Coeff (t) Effect -1.240 (3.0) -1.240 Variable Coeff (t) Effect Variable Price Index Car Ownership LnPrice-Rail-NonSeason 0.179 (8.0) 0.179 LnCars-LeisKmFuel LnPrice-Bus 0.068 (3.0) 0.068 Elasticity Type LnPrice-Car n.s - Base=FullElasticity LnPrice-UG n.s - ModeChoice-Leisure Study Source Base=Published... -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 Mode and Ticket Purpose Base=Bus Base=Commute-Peak Car-Trips -1.496 (8.4) -77.6% Business Car-Km -0.744 (4.9) -52.5% Leisure-OffPeak Car-FuelCons -0.557 (1.9) -42.7% NonComm Rail-Seasons n.s Rail-First Rail-Standard -0.232 (3.2) n.s - NonEB -20.7% All Coeff (t) Effect -0.574... (-0.85) -0.80 -0.70 (-1.00) -1.05 -1.20 (-1.00) -1.10 -1.02 PDFH LR Non Season First and Standard PDFH LR -0.40 (-0.70) -0.60 (-0.75) -0.60 (-0.90) First LR 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 Business SR Static LR DfT LR Commute SR and Static All LR DfT LR Leisure SR Static LR DfT LR -0.04 -0.07 -0.12 Trips Inter -0.07 -0.12...MODEL FORM META ANALYSIS RESULTS (I) Variable Coeff (t) Effect Variable Coeff (t) Effect Data Type Base=Static-Four Static-Quarter Static-Annual n.s LR-Quarter(Quarter) n.s - - LR-Quarter(Annual) n.s - 0.544 (9.2)... SR-Annual n.s - RP Choice n.s - LR-Four(Four) LR-Four(Annual) LR-Four(FourAnnual) 0.345 (6.9) +41.2% SP n.s - TP-Rail 0.539 (3.7) +71.4% TP-Bus 0.698 (8.5) +101.0% 0.793 (8.5) +121.0% 0.291 (1.6) +33.8% META ANALYSIS RESULTS (II) Variable Coeff ( t) Effect Variable Distance Category Area Type Base=Urban Base=NonUrban Coeff (t) Effect InterUrban-Rail n.s - UrbanPTE-Rail -0.521 (8.3) -40.6% InterUrban-Bus... RAIL ELASTICITIES Season Short PTE Short London Short Other Inter London Inter NonLon 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 -0.40 (-0.60) -0.60 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 -0.70 (-0.85) -0.80 -0.70 (-1.00) -1.05 -1.20 (-1.00) -1.10 -1.02 PDFH LR Non Season First and ... (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... (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) ...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) ?