social equity in distance based fares steven farber, university of utah gis in transit october...
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Social Equity in Distance Based Fares
Steven Farber, University of Utah
GIS in TransitOctober 16-17, 2013
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Background• UTA transitioning from a flat fare to a distance
based fare
• Title VI and EJ requirements (differential impacts)
• Different populations will be impacted differently since trip gen’s and distances travelled vary systematically with demographics
• Understanding of travel behavior required to assess differential impacts
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Fares and Sustainability
• Competing goals of transit agencyo Economic – Increase Revenueo Environmental – Decrease automobile useo Social – Provide transit service to those in need or
equally to all
• Distance based fares o Economically efficient (capturing external costs)o Socially beneficial (shorter but more frequent trips)o Environmentally detrimental (increased costs for long
distance discretionary riders)
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Fares and Equity
Equity
Fairness
Transit Fare Taxation
Flat fare per trip Fixed tax dollar amount regardless of income
/ Distance based fare (DBF)
Single tax rate for all
DBF with reduced cost of successive starts
Progressive tax rates (sliding scale)
Social equity in transportation is summarized by Sanchez as the distribution of “benefits and burdens from transportation projects equally across all income levels and communities”
Fairness: Whether the costs and benefits are equal after taking needs, means, and abilities into consideration.
Are we interested in equality or fairness?
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Research Questions• What are the social equity and fairness impacts of
a transition to DBF?
• How can travel behavior be used to assess social equity in this case?
• If DBFs are generally desirable, how can we find and address exceptions to this rule?
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Data• Utah Household Travel Survey
o Spring 2012o 1 day travel diaryo 9,155 Households o 27,046 Peopleo 101,404 Trips
• Filtered to only those residing in UTA’s core service area - 68% of respondents
• # daily of transit trips • Daily distance travelled by transit
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Ridership Percentage
Trips
Distance Travelled(miles)
Household Income No Answer 1.91 1.73 20.09 Under $35,000 5.17 1.94 13.25 $35,000 - $49,999 2.94 1.88 19.14 $50,000 - $99,999 2.24 1.85 20.56 $100,000 or more 2.17 1.86 24.51Hispanic Yes 4.38 1.89 17.39 No 2.60 1.88 19.60 Prefer not to answer 3.02 1.64 5.34Race White or Caucasian 2.50 1.89 19.93 All other 4.61 1.77 14.25Age 18-24 years old 6.87 1.82 17.47 25-34 years old 4.07 1.88 17.51 35-44 years old 3.37 1.84 24.19 45-54 years old 3.49 1.87 19.73 55-64 years old 3.13 1.88 17.82 >65 years old 1.59 2.08 13.91
Ridership Percentage
Trips
Distance Travelled(miles)
Education High school or less 3.73 1.85 13.08 Some College/Vocational/Associates
3.40 1.87 18.56
Bachelors 2.90 1.80 19.34 Grad/Post Grad 5.26 1.95 21.88Licensed Yes 3.14 1.86 20.39 No 13.67 1.96 11.34Number of vehicles Zero vehicle household 27.34 2.26 7.42 1 vehicle household 5.40 1.78 14.04 2 vehicle household 1.87 1.89 23.70 3+ vehicle household 1.99 1.81 23.21Home Ownership Rent 5.56 1.86 11.66 Own 2.17 1.87 22.77 Other 0.77 2.00 17.61Residence Type Single-family house (detached house)
2.17 1.88 22.82
Apartments 6.17 1.92 11.38 Other 3.34 1.74 13.89
Observed Travel Behavior
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Selection of Fares• UTA is considering fares that consist of a flat
component and a distance-based component
• For this study, we selected a revenue-neutral fareo $0.50 + $0.19 per mile
• Distance is measured as Euclidean distance so that users are not penalized by indirect network design
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Transit Trips
Distance Travelle
dFlat Fare
Distance Based Fare
Percentage
ChangeHousehold Income Under $35,000 1.94 13.25 4.85 3.49 -28.1% $35,000 - $49,999 1.88 19.14 4.70 4.58 -2.6% $50,000 - $99,999 1.85 20.56 4.63 4.83 4.5% $100,000 or more 1.86 24.51 4.65 5.59 20.1%Hispanic Yes 1.89 17.39 4.73 4.25 -10.1% No 1.88 19.6 4.70 4.66 -0.8%Race White or Caucasian
1.89 19.93 4.73 4.73 0.1%
All other 1.77 14.25 4.43 3.59 -18.8%Age 18-24 years old 1.82 17.47 4.55 4.23 -7.0% 25-34 years old 1.88 17.51 4.70 4.27 -9.2% 35-44 years old 1.84 24.19 4.60 5.52 19.9% 45-54 years old 1.87 19.73 4.68 4.68 0.2% 55-64 years old 1.88 17.82 4.70 4.33 -8.0% >65 years old 2.08 13.91 5.20 3.68 -29.2%
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Method• Estimate a joint model of transit trip generations
and distance travelled
• Spatially expanded coefficients – controls for contextual information not captured in the dataset
• Convert travel behavior to fares and compare results
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Ordered Model Estimates Continuous Model Estimates
B p-value
B p-value
Age less than 17 years 0.9052 0.0000 Constant -3.9564 0.0000
Age 18-24 years -0.1468 0.0607 Two transit trips 1.1045 0.0000
Age over 65 * 𝑢2 1.4356 0.0193 Three transit trips 1.5018 0.0000
Age over 65 * 𝑣2 0.8022 0.0167 Age over 65 -0.2700 0.1709
Mobility Limitation * 𝑣 -0.3858 0.0956 No children or retirees -0.1596 0.0821
Household w/ retirees -0.3449 0.0004 Student, em. < 25 hrs/week -0.2771 0.1868
Self employed 0.9011 0.0000 Unemployed/retired -0.2670 0.0483
Student, emp. 25+ hrs/week -0.4158 0.0000 High school or less * D_CBD -0.0072 0.0619
Unemployed/retired * 𝑢2 -1.1084 0.2099 Hispanic - Refusal -0.5133 0.0464
Unemployed/retired * 𝑢 1.8918 0.0003 Race: non-white * D_CBD 0.0199 0.0052
Grad. or post-grad. degree -0.3251 0.0000 Race: non-white * 𝑣 -0.4355 0.1926
Female 0.1842 0.0001 Zero vehicles * D_CBD -0.0132 0.0275
Hispanic 1.1440 0.0446 Income < $25K * 𝑢𝑣 -0.8834 0.0818
Hispanic * 𝑣 -1.2459 0.0902 Income $75-$100K -0.4831 0.0001
Hispanic * 𝑣2 -2.4449 0.0011 4 people 0.1759 0.1779
No driver’s license -1.3931 0.0000 3+ workers 0.2371 0.0917
No driver’s license * 𝑣 1.4272 0.0016 3+ children’s bikes 0.2400 0.1706
Zero vehicle household -0.7612 0.0000 5+ years in current res. 0.1163 0.1723
2 vehicle household 0.3455 0.0000 City, residential neigh. -0.1825 0.0500
3+ vehicle household 0.5623 0.0000 Distance to CBD 0.0522 0.0000
Income < $25K * 𝑢𝑣 -0.5827 0.1106 Distance to bus stop 0.1788 0.0003
Income – Refusal 0.1421 0.1002 𝑣 17.4178 0.0000
Household rents * D_CBD 0.0087 0.0001 𝑣2 -15.0180 0.0000
Household rents * 𝑢𝑣 -1.1271 0.0004 Joint Model Parameter Estimates
Household Tenure - Other 0.6485 0.1282
B p-value
Household Tenure - Refusal 0.8261 0.0700 𝜇1 -1.3672 0.0000
3+ workers -0.1580 0.0740 𝜇2 -1.5167 0.0000
3+ children’s bikes 0.2259 0.0186 𝜇3 -2.4753 0.0000
6+ people -0.2206 0.0076 𝜌 -0.1883 0.0625
Suburban mixed neighborhood -0.1226 0.0211 𝜎 0.8322 0.0000
Distance to Commuter Rail 0.0024 0.2466 𝑢2 0.4476 0.0410
Log-Likelihood: -3701.04; p(𝜒2)<0.0000; McFadden’s Adj. 𝜌ҧ2 : 0.1144; pseudo-𝑟2=0.5782; 𝑛=16071
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A B C D
0 10 Miles0 10 Miles0 10 Miles
Distance Travelled (Miles)
Bus Routes
> 55
0 10 Miles
< 2
2 - 3
3 - 4
4 - 5
5 - 6
6 - 7
7 - 8
8 - 9
9 - 10
10 - 14
14 - 18
18 - 22
22 - 26
26 - 30
30 - 35
35 - 40
40 - 45
45 - 55
Ref.Low Income & Education
Low Income & Elderly
Non-White
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A B C D
0 10 Miles0 10 Miles0 10 Miles0 10 Miles
Ratio of Expected Distance Based Fare to Flat Fare
< 0.35
0.35 - 0.45
0.45 - 0.55
0.55 - 0.65
0.65 - 0.75
0.75 - 0.85
0.85 - 0.95
0.95 - 1.05
1.05 - 1.25
1.25 - 1.50
1.50 - 2.00
2.00 - 2.50
2.50 - 3.00
3.00 - 4.00
> 4.00
Bus Routes
Ref.Low Income & Education
Low Income & Elderly
Non-White
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Census Tracts
Most Non-White
Most Hispanic
0.95 - 1.05
1.05 - 1.25
1.25 - 1.50
1.50 - 2.00
2.00 - 2.50
2.50 - 3.00
3.00 - 4.00
> 4.00
Cost Ratio
< 0.95
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Conclusions• Distance based fares generally result in cheaper
fares for those who need it most
• Pockets of mismatch exist – suburbanization of the poor poses a problem
• Burden on long-distance low-income travellers can be mitigated through reduced flat-fare components
• Changes in price are likely to shift wealthy discretionary riders back to their cars, but it may attract a plethora of new low-income riders
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Next Steps• Developing a GIS Decision Support System
• Analysts at UTA can compute fare surfaces for different demographic profiles and different fare structures
• Targeted studies of riders in particular at-risk neighborhoods identified by the DSS
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Acknowledgements• Xiao Li, Graduate RA• Keith Bartholomew, UofU• Antonio Páez, McMaster University• Khandker M. Nurul Habib, University of Toronto
• Utah Transit Authority
• Partial support from:o National Institute for Transportation and Communities (DTRT12-G-
UTC15-540)o National Science Foundation (BCS-1339462)