Potential MBTA Fare Increase
and Service Changes in 2012:
Scenario 3 Impact Analysis
A report produced for the Massachusetts Bay Transportation
Authority by the Central Transportation Planning Staff
Potential MBTA Fare Increase and
Service &KDQJHs in 2012: Scenario 3
Impact Analysis
Project Manager
Robert Guptill
Project Principal
Elizabeth Moore
Data Analysts
Grace King
Robert Guptill
Graphics
Robert Guptill
Cover Design
Kim Noonan
The preparation of this document was funded
by the Massachusetts Bay Transportation
Authority.
Produced for the Massachusetts Bay
Transportation Authority by the
Central Transportation Planning Staff
CTPS is directed by the Boston Region
Metropolitan Planning Organization.
The MPO is composed of state and
regional agencies and authorities, and
local governments.
March , 2012
To request additional copies of this document or
copies in an accessible format, contact:
Central Transportation Planning Staff
State Transportation Building
Ten Park Plaza, Suite 2150
Boston, Massachusetts 02116
(617) 973-7100
(617) 973-8855 (fax)
(617) 973-7089 (TTY)
[email protected]
www.bostonmpo.org
ABSTRACT
This analysis estimates various impacts of a potential scenario for MBTA
pricing and service aimed at reducing a projected budget deficit. The proposed
scenario raises most of its projected revenue through a fare increase; it also
includes service changes that eliminate some of the MBTA’s least costeffective services. The ridership, revenue, air quality, and environmental
justice impacts of these measures are estimated. Two different modeling
methodologies are used to produce these projections. The two models are
complementary; in addition, producing two sets of estimates provides a range
of possible impacts.
CTPS
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Acknowledgments
We wish to thank Charles Planck, Melissa Dullea, and Greg Strangeways of
the MBTA for their participation in the analysis of various fare increase and
service change scenarios.
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Boston Region MPO
CONTENTS
List of Exhibits
vii
EXECUTIVE SUMMARY
ix
1
INTRODUCTION
1
2
DESCRIPTION OF PROPOSED FARE INCREASE/SERVICE
CHANGE SCENARIO
3
2.1
Fare Structure Changes
3
2.2
Service Changes
5
2.2.1
Bus
5
2.2.2
Rapid Transit, Commuter Rail, Ferry, and THE RIDE
7
2.2.3
Summary of Service Changes
9
2.3
Fare Increase: Single-Ride Fares, Pass Prices, and Parking Rates
13
3
METHODS USED TO ESTIMATE RIDERSHIP AND REVENUE
19
3.1
CTPS Spreadsheet Model Approach
19
3.1.1
Modeling of Existing Ridership and Revenue
19
3.1.2
Estimation of Ridership Changes Resulting from a Fare Increase
21
3.2
Boston Region MPO Travel Demand Model Set Approach
22
3.3
Differences between the Two Estimation Methodologies
24
4
RIDERSHIP AND REVENUE IMPACTS
25
4.1
Overview of Results and Methodology
25
4.2
Spreadsheet Model Estimates
25
4.2.1
Projections
25
4.2.2
Sensitivity Analysis
26
4.2.3
Total Revenue Estimate
27
4.3
Regional Travel Demand Model Set Estimates
27
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v
CONTENTS
4.3.1
Projections
27
4.3.2
Total Revenue Estimate
28
4.4
Comparison of Model Results: Ranges of Projected Impacts
29
5
AIR QUALITY IMPACTS
33
5.1
Background
33
5.2
Estimated Air Quality Impacts
34
6
ENVIRONMENTAL JUSTICE IMPACTS
37
6.1
Definition of Environmental Justice Communities
37
6.2
Equity Determination
37
6.2.1
Transit Equity Metrics
38
6.2.2
Highway Congestion and Air Quality Equity Metrics
39
6.2.3
Accessibility Equity Metrics
40
6.2.4
Summary of Equity Impacts
40
7
CONCLUSIONS
43
APPENDIX: SPREADSHEET MODEL METHODOLOGY
A.1
Apportionment of Existing Ridership
A-1
A.2
Price Elasticity Estimation
A-1
A.3
Price Elasticity
A-3
A.4
Diversion Factors
A-4
A.5
Examples of Ridership and Revenue Calculations
A-5
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Boston Region MPO
EXHIBITS
Figure
2-1
Scenario 3 Weekday Bus, Rapid Transit, and Ferry Service Changes
10
2-2
Scenario 3 Saturday Bus, Rapid Transit, and Ferry Service Changes
11
2-3
Scenario 3 Sunday Bus, Rapid Transit, and Ferry Service Changes
12
2-4
Percentages of Riders Affected and Unaffected by the Proposed
Scenario 3 Service Changes
13
Table
E-1
2-1
Range of Revenue and Ridership Projections for the Proposed Fare
Increase and Service Changes
x
MBTA-Operated Bus Routes with Average Net Cost per Passenger
(Subsidy) Greater than 3.5 Times the Systemwide Average, by Day of
Week
5
2-2
Percentage of Service Affected
13
2-3
Key Single-Ride Fares: Existing and Proposed
14
2-4
Pass Prices: Existing and Proposed
15
2-5
Park-and-Ride Facility Rates: Existing and Proposed
16
2-6
Weighted Average Percentage Change in Average Fares, by Modal
Category, for Unlinked Trips
17
3-1
Price Elasticity Ranges Used in the Spreadsheet Model
22
4-1
Spreadsheet Model Estimates of Annual Ridership and Fare Revenue
Impacts
26
Spreadsheet Model Ranges of Estimates of Annual Ridership and Fare
Revenue Impacts Using Low and High Ranges of Elasticities
27
Spreadsheet Model Estimates of Total Revenue Change: Combined
Fare Revenue Gains and Saved Operating Costs
27
Travel Demand Model Set Estimates of Annual Ridership and Fare
Revenue Impacts
28
4-2
4-3
4-4
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EXHIBITS
4-5
Travel Demand Model Set Estimates of Total Revenue Change:
Combined Fare Revenue Gains and Saved Operating Costs
28
4-6
Range of Ridership Projections
30
4-7
Range of Fare Revenue Projections
30
4-8
Range of Projections for Total Revenue: Combined Fare Revenue
Gains and Saved Operating Costs
31
Projected Average Weekday Changes in Selected Pollutants
(Regionwide)
35
6-1
Existing and Projected Measures of Transit Equity Metrics
41
6-2
Existing and Projected Measures of Highway Congestion and Air
Quality Equity Metrics
41
6-3
Existing and Projected Measures of Accessibility Equity Metrics
42
A-1
AFC Fare Categories
A-1
A-2
AFC Modal Categories
A-2
A-3
Single-Ride and Pass Elasticities by Fare Type and Mode
A-3
5-1
KEYWORDS
ridership
revenue
air quality
environmental justice
fare increase
service reduction
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EXECUTIVE
SUMMARY
The Massachusetts Bay Transportation Authority (MBTA) faced a projected
$185 million operating budget deficit for fiscal year (FY) 2013 (July 1, 2012–
June 30, 2013). A series of one-time financial and administrative actions were
taken to reduce the projected deficit to $161 million. This report identifies a
combination of new fare revenues and operating cost savings through targeted
service reductions to address the remaining $161 million projected deficit. The
MBTA will continue to advance the operational and administrative efficiencies
undertaken since the implementation of forward funding in 2000 and
transportation reform in 2009, but it has limited means by which to raise
revenue sufficiently to close this operating budget deficit. The primary means
are raising fares, reducing service, or a combination of both. The MBTA has
developed three potential scenarios, each of which employs the combination
approach in different ways. Scenarios 1 and 2, described in a separate report,
raise enough revenue to close the FY 2013 budget gap.
Scenario 3, described in the present report, raises fares and reduces service less
than Scenarios 1 and 2 and consequently does not close the entire FY 2013
budget gap. It is projected to result in an increase in revenue of $88.3 million to
$91.6 million. This scenario, which was developed after the MBTA had
received significant public input in response to Scenarios 1 and 2, is now
feasible, as the Massachusetts Department of Transportation (MassDOT) has
identified additional funding sources that will meet the remainder of the
MBTA’s FY 2013 budget deficit.
Scenario 3 raises the majority of its projected revenue through a fare increase,
with the remainder of its revenue obtained by reducing service. This report
documents the projection of the impacts of this scenario on ridership, revenue,
air quality, and environmental justice communities.
The Central Transportation Planning Staff (CTPS) to the Boston Region
Metropolitan Planning Organization (MPO), using a spreadsheet model,
assisted the MBTA in determining the fare levels for each mode and fare
category that would be needed in the context of Scenario 3 to reach the revenue
targets the MBTA had established. It then used several analysis techniques to
estimate and evaluate the impacts of the scenario’s proposed fare increase and
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EXECUTIVE SUMMARY
service reductions. Both the spreadsheet model and the Boston Region MPO’s
regional travel demand model set were used to estimate the projected ridership
loss associated with the scenario and the net revenue change that would result
from the lower ridership and higher fares. By employing both techniques,
CTPS produced a range of estimates of potential impacts on ridership and
revenue. The travel demand model set was also used to predict the effects of
the fare increase on regional air quality and environmental justice.
Scenario 3 is projected to raise annual fare revenue by between $72.9 million
and $76.2 million through increasing fares by approximately 22.6 percent and
to save approximately $15.4 million in operating costs through reducing
service, for a total estimated gain in annual revenue of $88.3 million to $91.6
million. It is projected to result in a ridership loss of between 20.2 million and
21.4 million total systemwide annual unlinked trips, or approximately a 5.2-to5.5 percent loss.
A summary of the total ridership and revenue projections for Scenario 3 using
each estimation methodology is presented in the following table. As the table
indicates, CTPS estimated a smaller decrease in ridership and a smaller
increase in revenue when using the travel demand model set than when using
the spreadsheet approach. This relationship does not apply to all modes. The
travel demand model set estimated a greater decrease in ridership than the
spreadsheet model on the bus, commuter rail, and ferry modes, while the
opposite was true for the heavy and light rail modes. The greater ridership loss
estimated by the travel demand model set on the more expensive modes—
commuter rail and ferry—resulted in the smaller projected revenue gains on
these modes using this approach compared to the spreadsheet approach. This is
what caused the total revenue gain projected by the travel demand model set to
be less than that projected by the spreadsheet model.
TABLE E-1
Range of Revenue and Ridership Projections
for the Proposed Fare Increase and Service Changes
Annual Revenue and Ridership*
Existing
Spreadsheet Approach
Projected
Change % Chg.
Revenue
$483.1M
$574.7M
Ridership
386.4M
364.9M
+$91.6M +19.0%
-21.4M
-5.5%
Travel Demand Model
Projected
Change % Chg.
$571.4M
366.1M
+$88.3M +18.3%
-20.2M
-5.2%
*Ridership figures are based on unlinked transit trips.
Scenario 3 is projected to worsen air quality in terms of all pollutants. The
estimated magnitudes of the air quality impacts reflect the increases in vehiclemiles traveled (0.28 percent) and vehicle-hours traveled (0.55 percent)
projected to occur as transit riders divert to automobile trips and congestion
worsens as a result.
Equity was measured according to three categories of metrics: transit; highway
congestion and air quality; and accessibility. The transit metrics are average
fare, average walk-access time, average wait time, average in-vehicle travel
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Boston Region MPO
EXECUTIVE SUMMARY
time, number of transfers, and total transit trips. Scenario 3 has a smaller
increase in the average fare and a smaller estimated loss in transit riders for
environmental justice (EJ) communities than non-EJ communities. There is no
measurable difference between EJ and non-EJ communities in the change in
average walk-access, wait, or in-vehicle-travel times or in the change in the
number of transfers. As for local highway congestion and air pollution, the
increases in Scenario 3 are worse for EJ communities than non-EJ communities
(the existing levels of congestion and air pollution are also worse in EJ
communities than non-EJ communities). Finally, the differences between the
changes for EJ communities and those for non-EJ communities in the
accessibility of jobs, healthcare, and educational opportunities are so small that
they are not statistically significant, indicating that there would be no
perceptible difference.
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Introduction
The Massachusetts Bay Transportation Authority (MBTA) currently faces
serious financial problems. Its fiscal year (FY) 2013 (July 1, 2012–June 30,
2013) operating budget deficit was projected to total $185 million. A series of
one-time financial and administrative actions were taken to reduce the
projected deficit to $161 million. Given continued increases in operating
expenses, projected decreases in revenue, and growing debt service costs for
capital investments, the Authority will face continuous and growing deficits in
future years.
The primary methods that the MBTA has at its disposal for reducing deficits
are raising fares to increase revenue and reducing service to decrease operating
expenses, though the MBTA can raise revenue through other, less significant
means. The MBTA recently explored the impacts of various combinations of
potential fare-increase and service-reduction levels and decided to model two
scenarios with different combinations. The amount of the fare increase and
service reductions proposed by the MBTA for each of those scenarios was
determined by the objective of closing the projected FY 2013 budget deficit.
These two scenarios and their projected impacts are described in a separate
report. A third scenario has now been explored because the Massachusetts
Department of Transportation (MassDOT) has identified additional funding
sources that will help the MBTA to close its FY 2013 budget gap. This report
models this new third scenario, which was developed by the MBTA after
receiving significant input from the public regarding Scenarios 1 and 2.
The first step in the analysis process was for the Central Transportation
Planning Staff (CTPS) to the Boston Region Metropolitan Planning
Organization (MPO), in consultation with the MBTA, to determine the fare
level for each mode and fare category that would be needed to reach the
MBTA’s revenue targets given the estimated ridership loss due to the
scenario’s proposed service reductions. This was accomplished through an
iterative process in which CTPS utilized a spreadsheet model that was
specifically developed to analyze the degree to which ridership and revenue
would change if fares were raised by any given amount. CTPS also produced
alternative estimates of the impact on both ridership and revenue using the
Boston Region MPO’s regional travel demand model set. A comparison of the
CTPS
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1
INTRODUCTION
projections of each model provides a range of estimated impacts on ridership
and revenue. The impacts on air quality and environmental justice were
projected using the travel demand model set.
This report first presents detailed descriptions of the proposed scenario. It then
explains the estimation methods used by CTPS in its analysis and presents the
projected impacts of the proposed scenario on ridership, revenue, air quality,
and environmental justice communities. A brief summary of findings
concludes the report.
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Boston Region MPO
Description of
Proposed Fare
Increase/Service
Change Scenario
This chapter describes first the scenario’s fare structure, then its service
changes, and finally its fare increases.
2.1
FARE STRUCTURE CHANGES
Significant time and effort were expended, as part of developing the last fare
increase plan, implemented in 2007, to simplify the fare structure and to
modify it in ways that encourage riders to use certain fare media. Zoned local
bus routes were collapsed into a single local bus category. Fare zones and exit
fares were eliminated on the rapid transit system. The number of express bus
zones was reduced. The transfer price between bus and rapid transit was
reduced for CharlieCard users. CharlieTicket fares were priced at a higher rate
than CharlieCard fares. The Subway Pass was eliminated and the LinkPass was
introduced for use on both local bus routes and rapid transit routes at a reduced
price compared to the similar pass type that existed prior to the fare increase,
the Combo Pass. While the proposed Scenario 3 for FY 2013 raises prices,
eliminates services, and changes the fare structure, the suggested changes do
not conflict with or alter the structural changes or goals of the previous
restructuring.
One recommendation for fare structure changes in Scenario 3 concerns the
single-ride discounts for seniors and students for local bus and rapid transit. In
the current fare structure, the senior fare and student fare (regardless of
whether a CharlieCard or CharlieTicket is used) are set at approximately 33
percent and 50 percent, respectively, of the CharlieCard single-ride adult fare.
In Scenario 3, these ratios are set at approximately 40 percent for both seniors
and students, and the CharlieTicket single-ride adult fare, rather than the
CharlieCard fare, is used as the base rate. This change is in keeping with the
MBTA’s enabling legislation (MGL 161A, Section 5(e)) that links student and
senior discounts to the “adult cash fare,” which is equivalent to the
CharlieTicket adult fare.
Another change in the fare structure is proposed for THE RIDE. The current
fare structure charges a flat fare for any trip within THE RIDE’s service area.
THE RIDE currently serves riders living in any part of the towns to which the
MBTA provides fixed-route local bus or rapid transit service as well as riders
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DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
living in some nearby towns that do not have any fixed-route service. In
Scenario 3, THE RIDE’s base fare increases to twice the CharlieTicket local
bus adult fare, and a premium fare is charged for (a) trips to or from any area
outside of the service area mandated by the Americans with Disabilities Act
(ADA) (0.75-mile buffer from any local bus route or rapid transit station), (b)
trips before or after the service hours mandated by the ADA, and (c) same-day
and will-call 1 trips (which are outside the scope of the ADA).
Several other changes are also proposed. Tokens (used for MBTA fares prior to
2007 and still accepted in fare vending machines) are no longer accepted; this
reduces administrative costs. A 7-Day Student Pass is introduced to accompany
the existing 5-Day Student Pass. Both Student Passes will have all-day validity,
eliminating the existing 11:00 PM limit on use of the Student Pass. As with the
5-Day Student Pass, the 7-Day Student Pass is valid on local bus, rapid transit,
inner and outer express bus, and commuter rail in zones up to Zone 2.
Scenario 3 also changes the structure of multi-ride tickets. The 12-ride ticket
on commuter rail is replaced by a 10-ride ticket, and the 60-ride ticket on the
ferry is eliminated. Therefore, commuter rail and ferry will have the same
multi-ride ticket structure: a 10-ride adult ticket and a 10-ride reduced-fare
ticket. On neither commuter rail nor ferry do the multi-ride tickets receive a
multi-ride discount. The “Group Fare” on commuter rail is also eliminated,
because of its limited usage and the cost of providing a separate product. The
“Family Fare” on commuter rail remains, but its use is limited to off-peak
trains. Finally, the duration of the validity of single- and multi-ride tickets is
reduced from 180 days to 14 days and 30 days, respectively. Note that a roundtrip ticket is considered to be two single-ride tickets, each with the single-ride
duration of validity.
A surcharge is currently charged for commuter rail tickets that are sold
onboard the trains. This policy is to charge a $2.00 surcharge during the peak
time periods and a $1.00 surcharge during the off-peak time periods. Scenario
3 sets fares for single-ride tickets that are sold onboard the trains. The fare for
such a ticket equals the price for the same zonal ticket if sold before boarding
the train plus $3.00. There is no differentiation between peak and off-peak time
periods. The $3.00 is added per ticket, not per transaction. In other words, the
price of multiple onboard tickets bought by a single person would equal the
number of tickets multiplied by the total single-ride onboard ticket price; that
is, $3.00 would be added to the single-ride pre-sold fare for each ticket. For
example, for two tickets with a pre-sold single-ride fare of $5.00 each, the total
onboard cost would be $16.00.
1
Will-call trips are a type of same-day trip in which, although the passenger selects a time range for pickup before the day of the trip, the passenger only specifies the exact pick-up time on the day of the trip.
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DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
2.2
SERVICE CHANGES
2.2.1
BUS
For several of the bus routes that currently have a net cost per passenger
greater than 3.5 times the systemwide average, 2 Scenario 3 proposes a
reduction in frequency and/or revisions of routing or service, or complete
elimination. It also proposes routing revisions for three other routes.
In determining net cost per passenger, weekday, Saturday, and Sunday services
are assessed separately. The systemwide averages are $1.42 on weekdays,
$1.37 on Saturday, and $1.30 on Sunday, resulting in evaluation thresholds of
$4.97 on weekdays, $4.80 on Saturday, and $4.55 on Sunday. According to
these thresholds, 13 weekday bus routes, 5 Saturday bus routes, and 6 Sunday
bus routes fail. These routes are listed in Table 2-1, and the net cost per
passenger is given for each route for the day(s) of the week on which it fails
the cost threshold.
TABLE 2-1
MBTA-Operated Bus Routes with Average Net Cost per Passenger (Subsidy)
Greater than 3.5 Times the Systemwide Average, by Day of Week
Route #
18
37/38
48
52
59
170
171
217
245
325
351
354
355
436
439
451
468
500
554
555
CT3
Route Description
Ashmont Station - Andrew Station
Baker & Vermont Streets - Forest Hills Station
Centre & Eliot Streets - Jamaica Plain Loop
Dedham Mall - Watertown Yard
Needham Junction - Watertown Square
Oak Park - Dudley Station (Limited Service)
Logan Airport - Dudley Station Sunrise
Wollaston Station - Ashmont Station via Wollaston Beach
Quincy Center Station - Mattapan Station
Elm Street - Haymarket Station
Oak Park - Alewife Station
Woburn Line - State Street
Mishawum Station - State Street
Danvers Sq - Central Sq Lynn
Bass Point Nahant - Central Sq Lynn
North Beverly - Salem Depot
Danvers Square - Salem Depot (Limited Service)
Riverside Station - Federal & Franklin Streets
Waverly Square - Federal & Franklin Streets
Riverside Station - Federal & Franklin Streets
Longwood Medical Area - Andrew Station
Weekday
Saturday
$6.34
$6.14
$7.17
Sunday
$5.51
$5.27
$4.74
$5.56
$5.07
$7.19
$7.14
$5.56
$7.17
$6.33
$5.16
$13.14
$5.40
$9.76
$6.34
$5.89
$10.51
$6.82
$8.68
$5.39
$5.11
A service change is only proposed for some of the routes listed in Table 2-1 (a
summary is provided in Section 2.2.3). Three weekday routes are proposed for
complete elimination: Routes 48, 355, and 500. All three routes are eliminated
2
Net cost per passenger is the difference between the cost to operate the route and the average revenue
collected on the route, divided by the number of passengers. The MBTA’s Service Delivery Policy (SDP)
establishes a net-cost-per-passenger standard of three times the system average to identify routes that are
considered deficient and are subject to review for potential modifications. Using 3.5 times the systemwide
average as a net-cost-per-passenger threshold captures fewer routes than the net-cost-per-passenger
standard in the SDP.
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DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
because of their high net cost per passenger and low ridership, and the fact that
other transit services are nearby. 3 These eliminations would likely require
many of these passengers to walk a greater distance to access other transit
services or to transfer between services at a greater rate. As an alternative for
passengers using one of the four daily reverse-commute trips on Route 355, it
is recommended that the inbound commuter rail train on the Lowell Line that
passes through Mishawum Station around 3:36 PM stop at the station. As for
weekend service, five routes on Saturday (Routes 48, 52, 245, 451, and 554)
and four routes on Sunday (Routes 18, 37/38, 245, and 436) are recommended
for elimination. Collectively, the eliminations proposed on these selected
routes affect approximately 65,000 annual weekday unlinked trips, 40,000
annual Saturday unlinked trips, and 28,000 annual Sunday unlinked trips, for a
total of 133,000 annual trips, or 0.12 percent of all annual MBTA bus unlinked
trips.
Route revisions are proposed for three of the routes listed in Table 2-1: Routes
217, 439, and 555. For Route 217, the route segment serving Wollaston Beach
is recommended for elimination. However, several school trips are combined
with Route 217, which extends service on these trips to Ashmont Station. For
Route 439, the recommendations are the elimination of service between Vinnin
Square and Central Square, Lynn, and the extension of service beyond Central
Square, Lynn, to Wonderland Station for 1.5 round-trips out of each day’s
trips. Route 555 is merged into the schedule of Route 553 and the route
terminus moved from Riverside Station to Central Square, Waltham. This
variation of Route 553 would still serve Copley Square. Finally, it is also
recommended that weekday Haymarket services on Routes 441, 442, and 455
terminate at Wonderland Station, replicating the weekend routing; while these
routes do not have a net cost per passenger greater than 3.5 times the
systemwide average, the revision of these routes would save nearly $0.5
million in annual operating costs. Passengers on these routes would need to
transfer to the Blue Line, but the fare on these bus routes would be lowered
from the current Inner Express fare to a Local Bus fare. Passengers still
wanting a one-seat ride to and from downtown Boston could use Routes 448,
449, and 459.
In addition to the route revisions described above, Scenario 3 recommends the
elimination of midday-only weekday service for Routes 354 and 451. This
proposal maintains peak-period weekday service on these routes. When the
unlinked trips on these two routes are added to the unlinked trips of riders
affected by the routing revisions (on Routes 217, 439, 441, 442, 455, and 555),
the annual weekday total is approximately 297,000, or 0.28 percent of all
annual MBTA bus unlinked trips.
Changes to the frequency of service are recommended for five routes listed in
Table 2-1. Weekday peak service is maintained for Route 52, but midday
frequency is reduced from 45 minutes to 90 minutes. The total number of trips
3
Parts of Route 48 are also served by the Orange Line and Routes 22, 29, 41, and 44; Route 355 passengers
can use commuter rail; Route 500 passengers can use the Green Line D Branch.
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Boston Region MPO
DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
on Route 217 is reduced from 11 to 4.5 round-trips. Frequency on Route 351 is
reduced from 30 minutes to 45 minutes. The total number of trips on Route 439
is reduced from 9 to 5 round-trips, with 1.5 round-trips serving the route’s
extension to Wonderland Station. Weekday peak service is maintained for
Route CT3, but midday frequency is reduced from 30 minutes to 60 minutes.
Collectively, the frequency reductions proposed on these selected routes affect
approximately 69,000 annual weekday unlinked trips, or 0.06 percent of all
annual MBTA bus unlinked trips. On Saturday, the only frequency reduction is
proposed for Route 465, from 70 minutes to 120 minutes. With the proposed
elimination of Route 451 service and the fact that buses are currently shared
between Routes 451 and 465, the reduction in Route 465 frequency would
avoid having Route 465 buses sit idle between trips. This proposal affects
approximately 17,000 annual Saturday unlinked trips.
For private bus routes (routes that are part of the Private Carrier Bus Program
or the Suburban Bus Program, under which bus service is funded by the
MBTA but operated by a private contractor), two changes are recommended.
First, the private-carrier route serving Medford (Route 710) is recommended
for elimination, since a portion of this route would still be served by MBTA
Route 134. Second, a reduction of 50 percent is recommended for the subsidy
provided to all Suburban Bus Program recipients. While it is unknown how this
reduction in subsidies might affect recipients’ decisions regarding whether to
modify or to not operate service, this policy could potentially affect all
passengers currently riding these routes. The sum of annual unlinked trips on
Route 710 and all Suburban Bus Program routes is approximately 169,000 on
weekdays and 4,000 on Saturdays, for a total of 173,000 annual trips, or 23.5
percent of all annual unlinked trips on routes subsidized through the Private
Carrier Bus and Suburban Bus Programs. This total is 0.16 percent of annual
unlinked trips on all bus routes (both MBTA and private bus routes).
Figure 2-1 presents a map of weekday service that shows MBTA and private
bus routes and the service changes proposed in Scenario 3. Figures 2-2 and 2-3
do the same for Saturday and Sunday services, respectively. The figures also
present estimates of the numbers of unlinked trips that would be affected by the
proposed service changes.
2.2.2
RAPID TRANSIT, COMMUTER RAIL, FERRY, AND THE RIDE
Two changes are proposed in Scenario 3 for rapid transit. First, the elimination
of weekend service on the Green Line E Branch between Brigham Circle and
Heath Street is recommended. An average of 7.3 passengers per trip use this
segment of the Green Line on Saturday, and on Sunday this average is 5.1
passengers per trip. It is assumed that these passengers could use Route 39,
which duplicates service on much of the Green Line, including between
Brigham Circle and Heath Street. The second proposed change affects the
Mattapan High-Speed Line on Saturday between 6:00 AM and 10:00 AM and
between 8:00 PM and 1:00 AM, and on Sunday all day. It is recommended that
the frequency be reduced from every 11–13 minutes to every 23–26 minutes
CTPS
3/28/2012
7
DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
(this is the frequency that is estimated to result from the elimination of one of
the two trains serving the line during these time periods while maintaining
coordination with every other Red Line train at Ashmont Station). Ridership
during these time periods currently averages between eight and nine passengers
per trip. The combined existing annual unlinked trips on the Green Line E
Branch between Brigham Circle and Heath Street and on the Mattapan HighSpeed Line during the defined time periods is 116,000 on Saturday and 89,000
on Sunday, for a total of 205,000 annual trips, or 0.31 percent of all annual
unlinked trips on light rail.
Of the ferry routes, the F1 service between Hingham and Rowes Wharf and the
F2H service between Quincy, Hull, Logan Airport, and Long Wharf currently
operate only on weekdays, and the F2 service between Quincy, Logan Airport,
and Long Wharf and the F4 Inner Harbor Ferry service currently operate on
weekdays, Saturdays, and Sundays. It is recommended in Scenario 3 that
weekend F2 service be eliminated, but no service changes are proposed for the
other ferry services. It is assumed that weekend F2 riders could use the Red
Line. Existing Saturday ridership on the F2 service is approximately 42,000
annual trips; existing Sunday ridership is approximately 29,000. The combined
weekend ridership total is 71,000, or 5.5 percent of all annual trips on ferry
routes.
The elimination of weekend service is recommended for the commuter rail
lines with the lowest weekend ridership totals. These are the Greenbush Line
and the Plymouth/Kingston Line on Saturday and Sunday, and the Needham
Line on Saturday (the Needham Line already does not operate on Sunday).
Together, these lines serve approximately 179,000 annual trips on Saturday
and 113,000 annual trips on Sunday. The combined weekend ridership total is
292,000, or 0.79 percent of all annual trips on commuter rail.
Finally, while no service reductions per se are proposed for THE RIDE, the
increase in fares and the institution of a premium-fare zone are estimated to
reduce the demand for service in Scenario 3, saving the MBTA the cost of
serving the trips no longer made. Based on an analysis of a sample day of
RIDE trips in which the trip pick-up and drop-off locations are linked, 4 it was
estimated that 11.7 percent of existing RIDE trips would fall into the premium4
Linking the trip pick-up and drop-off locations permits an analysis of not only how many trips are located
outside the required ADA buffer, but also how many trips cross the border of this buffer into the premiumfare zone, for which the ADA permits a premium fare to be charged. According to the sample day, 1.1
percent of RIDE trips had both a pick-up and drop-off location outside the ADA buffer and 10.7 percent
had one pick-up or drop-off location inside the buffer and the corresponding drop-off or pick-up location
outside the buffer. An analysis of an annual total of all RIDE pick-up and drop-off locations that are not
linked indicated that 6.4 percent of locations were outside the ADA buffer. If one assumes, from the sample
day, that approximately 10 percent of all premium fares have both the pick-up and drop-off locations
outside the ADA buffer (1.1 percent divided by 10.7 percent), then approximately 90 percent of the 6.4
percent of premium-fare locations in the annual total, or 5.7 percent, could be assumed to have either a
corresponding pick-up or drop-off location within the ADA buffer. The sum of 6.4 percent and 5.7 percent,
which represents the percentage of locations associated with trips charged at the premium fare, is 12.1
percent, which is close to the 11.7 percent estimated using the sample day. Based on this comparison of the
annual and the sample-day trips, sufficient confidence was felt in the percentage from the sample day.
8
3/28/2012
Boston Region MPO
DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
fare category.
Figure 2-1 presents a map of weekday service that shows rapid transit and ferry
routes and the service changes proposed in Scenario 3. Figures 2-2 and 2-3 do
the same for Saturday and Sunday services, respectively. The figures also
present estimates of the numbers of unlinked trips that would be affected by the
proposed service changes.
2.2.3 SUMMARY OF SERVICE CHANGES
In summary, Scenario 3 includes the following service changes:
• Bus
o Eliminate the following routes: Weekday: 48, 355, and 500.
Saturday: 48, 52, 245, 451, and 554. Sunday: 18, 37/38, 245,
and 436.
o Revise the routing: Weekday: 217, 439, 441, 442, 455, and 555
o Eliminate midday service: Weekday: 354 and 451
o Reduce the frequency: Weekday: 52, 217, 351, 439, and CT3
• Rapid Transit
o Eliminate weekend service on the Green Line E Branch between
Brigham Circle and Heath Street
o Reduce frequency on the Mattapan High-Speed Line on
Saturday from 6:00 AM to 10:00 AM and from 8:00 PM to
1:00 AM, and all day Sunday
• Commuter Rail: Eliminate the following service:
o Saturday: Needham Line, Plymouth/Kingston Line, and
Greenbush Line
o Sunday: Plymouth/Kingston Line and Greenbush Line
• Ferry: Eliminate weekend service on Quincy Ferry (Route F2)
• Private Bus: Eliminate Private Carrier Bus Program in Medford (Route
710) and reduce subsidies by 50 percent to Suburban Bus Program in
all locations (Bedford, Beverly, Boston [Mission Hill], Burlington,
Dedham, and Lexington)
Figures 2-1, 2-2, and 2-3 all show the numbers of riders while Figure 2-4 shows
the relative percentages of riders on each mode that are affected by the proposed
service changes (eliminations, revisions, and frequency reductions) in Scenario
3. Table 2-2 summarizes four measures of service that are affected by the
proposed scenario. The four measures are unlinked trips (the number of trips
riders take on each transit vehicle), passenger miles (the total number of miles
traveled on those unlinked trips), vehicle revenue hours (the total number of
hours all transit vehicles are in service), and vehicle revenue miles (the total
number of miles traveled by those transit vehicles in service). The table also
presents the number of MBTA jobs that are estimated to be lost and the number
of MBTA buses that could be removed from service. Scenario 3 generally
reduces bus and commuter rail service on routes traversing longer distances,
which is why the percentages of passenger miles, vehicle revenue hours, and
vehicle revenue miles affected are greater than the percentage of unlinked trips.
CTPS
3/28/2012
9
TEWKSBURY
WENHAM
MIDDLETON
NORTH READING
DANVERS
MANCHESTER
GLOUCESTER
FIGURE 2-1
Scenario 3 Weekday Bus, Rapid Transit, and
Ferry Service Changes
BEVERLY
WILMINGTON
BILLERICA
LYNNFIELD
READING
Route Eliminations (65,000 annual trips):
- Eliminate routes: 48, 355, and 500
PEABODY
SALEM
BEDFORD
BURLINGTON
WAKEFIELD
MARBLEHEAD
WOBURN
SAUGUS
STONEHAM
CONCORD
LINCOLN
ARLINGTON
BELMONT
WALTHAM
MEDFORD
ARLINGTON
SAUGUS
MALDEN
MEDFORD
REVERE
EVERETT
MALDEN
NAHANT
REVERE
EVERETT
SOMERVILLE
MELROSE
WINCHESTER
SWAMPSCOTT
MELROSE
WINCHESTER
LEXINGTON
LYNN
BELMONT
SOMERVILLE
WINTHROP
CAMBRIDGE
CHELSEA
WATERTOWN
WINTHROP
CAMBRIDGE
WATERTOWN
CHELSEA
WESTON
NEWTON
NEWTON
BROOKLINE
BROOKLINE
HULL
NEEDHAM
Legend
MILTON QUINCY
DEDHAM
QUINCY
MILTON
DOVER
NORWOOD
CANTON
Ferry: Maintained Service
SCITUATE
WEYMOUTH
Reduced-Frequency Service
RANDOLPH
Midday-Only Eliminated Service
NORWELL
WALPOLE
HOLBROOK
SHARON
NORFOLK
Rapid Transit: Maintained Service
HINGHAM
BRAINTREE
MEDFIELD
Bus: Maintained Service
COHASSET
WESTWOOD
STOUGHTON
ROCKLAND
AVON
BROCKTON
ABINGTON
HANOVER
Reduce Frequency (69,000 annual trips):
- Route 52: From 45 to 90 minutes in midday
- Route 217: From 11 to 4.5 round-trips
- Route 351: From 30 to 45 minutes
- Route 439: From 9 to 5 round-trips; 1.5 round-trips to
serve Wonderland
- Route CT3: From 30 to 60 minutes in midday
Eliminate Private Carrier Bus Program in Medford
(Route 710) and reduce Suburban Bus Program
subsidies by 50% in all locations (Bedford, Boston
[Mission Hill], Beverly, Burlington, Dedham, and
Lexington) (169,000 annual trips)
BOSTON
BOSTON
WELLESLEY
Route Revisions (297,000 annual trips):
- Route 217: Eliminate Wollaston Beach section
- Route 354: Eliminate midday service
- Route 439: Eliminate service between Central Square
(Lynn) and Vinnin Square; extend service to Wonderland
- Route 441: Eliminate service between Wonderland and
Haymarket
- Route 442: Eliminate service between Wonderland and
Haymarket
- Route 451: Eliminate midday service
- Route 455: Eliminate service between Brown Circle and
Haymarket and terminate at Wonderland
- Route 555: Change terminus from Riverside to Central
Square (Waltham)
MARSHFIELD
PEMBROKE
0
1
2
±
4 Miles
Eliminated Service
Suburban Bus Program Service
CTPS - 3/28/2012
TEWKSBURY
WENHAM
MIDDLETON
NORTH READING
DANVERS
MANCHESTER
GLOUCESTER
FIGURE 2-2
Scenario 3 Saturday Bus, Rapid Transit, and
Ferry Service Changes
BEVERLY
WILMINGTON
BILLERICA
LYNNFIELD
READING
Route Eliminations (82,000 annual trips):
- Eliminate routes: 48, 52, 245, 451, 554 and
Quincy ferry (Route F2)
PEABODY
SALEM
BEDFORD
BURLINGTON
WAKEFIELD
MARBLEHEAD
WOBURN
STONEHAM
CONCORD
LINCOLN
ARLINGTON
BELMONT
WALTHAM
MEDFORD
ARLINGTON
MALDEN
SOMERVILLE
MALDEN
MEDFORD
REVERE
BELMONT
CHELSEA
SOMERVILLE
CHELSEA
WINTHROP
CAMBRIDGE
Reduce Frequency (27,000 annual trips):
- Route 465: From 70 to 120 minutes
- Mattapan High-Speed Line: From 11-13 to 23-26 minutes,
6:00 to 10:00 AM and 8:00 PM to 1:00 AM
Eliminate Private Carrier Bus Program in Medford
(Route 710) and reduce Suburban Bus Program
subsidies by 50% in both locations (Boston [Mission Hill]
and Beverly) (4,000 annual trips)
WATERTOWN
WINTHROP
CAMBRIDGE
WATERTOWN
SAUGUS
EVERETT
NAHANT
REVERE
EVERETT
MELROSE
WINCHESTER
SWAMPSCOTT
MELROSE
WINCHESTER
LEXINGTON
LYNN
SAUGUS
Route Revisions (107,000 annual trips):
- Green Line E Branch: Eliminate service between
Brigham Circle and Heath Street
WESTON
NEWTON
BROOKLINE
BROOKLINE
BOSTON
BOSTON
WELLESLEY
HULL
NEEDHAM
DEDHAM
COHASSET
WESTWOOD
Bus: Maintained Service
HINGHAM
BRAINTREE
NORWOOD
MEDFIELD
Legend
QUINCY
MILTON
DOVER
QUINCY
CANTON
Rapid Transit: Maintained Service
SCITUATE
WEYMOUTH
Ferry: Maintained Service
RANDOLPH
Reduced-Frequency Service
NORWELL
WALPOLE
HOLBROOK
SHARON
NORFOLK
STOUGHTON
ROCKLAND
AVON
ABINGTON
BROCKTON
HANOVER
MARSHFIELD
PEMBROKE
0
1
2
±
4 Miles
Eliminated Service
Suburban Bus Program Service
CTPS - 3/28/2012
TEWKSBURY
WENHAM
MIDDLETON
NORTH READING
DANVERS
MANCHESTER
GLOUCESTER
FIGURE 2-3
Scenario 3 Sunday Bus, Rapid Transit, and
Ferry Service Changes
BEVERLY
WILMINGTON
BILLERICA
LYNNFIELD
READING
Route Eliminations (57,000 annual trips):
- Eliminate routes: 18, 37/38, 245, 436 and
Quincy ferry F2
PEABODY
SALEM
BEDFORD
BURLINGTON
WAKEFIELD
MARBLEHEAD
WOBURN
CONCORD
LINCOLN
ARLINGTON
BELMONT
WALTHAM
MEDFORD
SAUGUS
MALDEN
MEDFORD
ARLINGTON
REVERE
Reduce Frequency (21,000 annual trips):
- Mattapan High-Speed Line: From 11-13 to 23-26 minutes
all day
EVERETT
MALDEN
NAHANT
REVERE
EVERETT
SOMERVILLE
MELROSE
WINCHESTER
SWAMPSCOTT
MELROSE
WINCHESTER
LEXINGTON
LYNN
SAUGUS
STONEHAM
Route Revisions (68,000 annual trips):
- Green Line E Branch: Eliminate service between
Brigham Circle and Heath St
BELMONT
WINTHROP
CAMBRIDGE
CHELSEA
WATERTOWN
WINTHROP
CAMBRIDGE
WATERTOWN
CHELSEA
SOMERVILLE
WESTON
NEWTON
NEWTON
BROOKLINE
BROOKLINE
BOSTON
BOSTON
WELLESLEY
HULL
NEEDHAM
QUINCY
MILTON
DEDHAM
QUINCY
MILTON
DOVER
COHASSET
WESTWOOD
BRAINTREE
NORWOOD
MEDFIELD
Legend
HINGHAM
CANTON
Bus: Maintained Service
SCITUATE
WEYMOUTH
Rapid Transit: Maintained Service
RANDOLPH
Ferry: Maintained Service
NORWELL
WALPOLE
HOLBROOK
SHARON
NORFOLK
STOUGHTON
ROCKLAND
AVON
ABINGTON
BROCKTON
HANOVER
MARSHFIELD
PEMBROKE
0
1
2
±
4 Miles
Reduced-Frequency Service
Eliminated Service
CTPS - 3/28/2012
DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
TABLE 2-2
Percentage of Service Affected
Measure
Unlinked Trips
Passenger Miles
Vehicle Revenue Hours
Vehicle Revenue Miles
MBTA Jobs Lost
Buses Removed
2.3
Number
1,212,242
8,692,607
60,677
1,076,494
15
3
Percent
0.3%
0.5%
1.2%
1.4%
FARE INCREASE: SINGLE-RIDE FARES, PASS PRICES, AND
PARKING RATES
Table 2-3 presents the key existing and proposed single-ride fares for each fare
category, along with the percentage change in price from the existing to the
proposed price. Table 2-4 presents the existing and proposed pass prices for
each pass category, along with the percentage change in price from the existing
to the proposed price. Table 2-5 presents the existing and proposed parking
rates for each parking facility, along with the percentage change in price from
the existing to the proposed price.
CTPS
3/28/2012
13
DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
TABLE 2-3
Key Single-Ride Fares: Existing and Proposed
Fare Category
CharlieCard
Adult
Local Bus
Rapid Transit
Bus + RT*
Inner Express
Outer Express
Senior
Local Bus
Rapid Transit
Bus + RT*
Student
Local Bus
Rapid Transit
Bus + RT*
CharlieTicket
Adult
Local Bus
Rapid Transit
Bus + RT*
Inner Express
Outer Express
Commuter Rail**
Zone 1A
Zone 1
Zone 2
Zone 3
Zone 4
Zone 5
Zone 6
Zone 7
Zone 8
Zone 9
Zone 10***
InterZone 1
InterZone 2
InterZone 3
InterZone 4
InterZone 5
InterZone 6
InterZone 7
InterZone 8
InterZone 9***
InterZone 10***
Ferry
F1
F2: Boston
F2: X-Harbor
F2: Logan
Inner Harbor
THE RIDE
ADA Territory
Premium Territory***
Existing
Proposed
% Chg.
$ Chg.
$1.25
$1.70
$1.70
$2.80
$4.00
$1.50
$2.00
$2.00
$3.50
$5.00
20.0%
17.6%
17.6%
25.0%
25.0%
$0.25
$0.30
$0.30
$0.70
$1.00
$0.40
$0.60
$0.60
$0.75
$1.00
$1.00
87.5%
66.7%
66.7%
$0.35
$0.40
$0.40
$0.60
$0.85
$0.85
$0.75
$1.00
$1.00
25.0%
17.6%
17.6%
$0.15
$0.15
$0.15
$1.50
$2.00
$3.50
$3.50
$5.00
$2.00
$2.50
$4.50
$4.50
$6.50
33.3%
25.0%
28.6%
28.6%
30.0%
$0.50
$0.50
$1.00
$1.00
$1.50
$1.70
$4.25
$4.75
$5.25
$5.75
$6.25
$6.75
$7.25
$7.75
$8.25
N/A
$2.00
$2.25
$2.50
$2.75
$3.00
$3.50
$4.00
$4.50
N/A
N/A
$2.00
$5.50
$6.00
$6.75
$7.25
$8.00
$8.75
$9.25
$10.00
$10.50
$11.00
$2.50
$3.00
$3.25
$3.50
$4.00
$4.50
$5.00
$5.50
$6.00
$6.50
17.6%
29.4%
26.3%
28.6%
26.1%
28.0%
29.6%
27.6%
29.0%
27.3%
N/A
37.5%
33.3%
30.0%
36.4%
41.7%
35.7%
31.3%
27.8%
N/A
N/A
$0.30
$1.25
$1.25
$1.50
$1.50
$1.75
$2.00
$2.00
$2.25
$2.25
N/A
$0.50
$0.75
$0.75
$0.75
$1.00
$1.00
$1.00
$1.00
N/A
N/A
$6.00
$6.00
$10.00
$12.00
$1.70
$8.00
$8.00
$13.00
$16.00
$3.00
33.3%
33.3%
30.0%
33.3%
76.5%
$2.00
$2.00
$3.00
$4.00
$1.30
$2.00
N/A
$4.00
$5.00
100.0%
N/A
$2.00
N/A
* “Bus + RT” indicates the linked-trip price of a trip on both local bus and rapid transit.
** Multi-ride and onboard ticket prices are described in Section 2.1, Fare Structure Changes.
*** This fare category does not currently exist; therefore, both the existing price and percent
change are marked as “N/A.”
14
3/28/2012
Boston Region MPO
DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
TABLE 2-4
Pass Prices: Existing and Proposed
Pass Category
Local Bus
LinkPass
Senior/TAP
Student 5-Day
Student 7-Day*
1-Day
7-Day
Inner Express
Outer Express
Commuter Rail
Zone 1A
Zone 1
Zone 2
Zone 3
Zone 4
Zone 5
Zone 6
Zone 7
Zone 8
Zone 9
Zone 10*
InterZone 1
InterZone 2
InterZone 3
InterZone 4
InterZone 5
InterZone 6
InterZone 7
InterZone 8
InterZone 9*
InterZone 10*
Commuter Boat
Existing
$40.00
$59.00
$20.00
$20.00
N/A
$9.00
$15.00
$89.00
$129.00
Proposed
$48.00
$70.00
$28.00
$25.00
$28.00
$11.00
$18.00
$110.00
$160.00
% Chg.
20.0%
18.6%
40.0%
25.0%
N/A
22.2%
20.0%
23.6%
24.0%
$ Chg.
$8.00
$11.00
$8.00
$5.00
N/A
$2.00
$3.00
$21.00
$31.00
$59.00
$135.00
$151.00
$163.00
$186.00
$210.00
$223.00
$235.00
$250.00
$265.00
N/A
$65.00
$77.00
$89.00
$101.00
$113.00
$125.00
$137.00
$149.00
N/A
N/A
$198.00
$70.00
$173.00
$189.00
$212.00
$228.00
$252.00
$275.00
$291.00
$314.00
$329.00
$345.00
$82.00
$100.00
$109.00
$118.00
$134.00
$151.00
$167.00
$184.00
$201.00
$218.00
$262.00
18.6%
28.1%
25.2%
30.1%
22.6%
20.0%
23.3%
23.8%
25.6%
24.2%
N/A
26.2%
29.9%
22.5%
16.8%
18.6%
20.8%
21.9%
23.5%
N/A
N/A
32.3%
$11.00
$38.00
$38.00
$49.00
$42.00
$42.00
$52.00
$56.00
$64.00
$64.00
N/A
$17.00
$23.00
$20.00
$17.00
$21.00
$26.00
$30.00
$35.00
N/A
N/A
$64.00
* This fare category does not currently exist; therefore, both the existing price and percent
change are marked as “N/A.”
The overall price increase across all modes and fare/pass categories is
approximately 22.6 percent. This systemwide average is based on the weighted
averages that were calculated by multiplying the percentage change in price for
each fare/pass category by the existing ridership in that category and dividing
by total existing modal ridership. Table 2-6 presents these weighted average
percentage increases by modal category. Note that the percentage changes in
price can differ between modes that are similarly priced (such as local bus and
the Silver Line–Washington Street, or subway and surface light rail) because of
differences in how the riders on these modes pay for their trips.
In Scenario 3, the percentage change in prices (Table 2-6) is relatively
consistent across modal categories except for ferry and THE RIDE. The latter
faces a significant price increase with the introduction of the premium fare and
the change in how the base fare is defined. The large price increase for ferry is
driven by the percentage changes in the prices for the F1 and F4 services.
Commuter rail receives the next-greatest percentage price increase; this is
meant to compensate for the fact that no increase in commuter rail park-andride facility rates, except for the Route 128 facility, is proposed.
CTPS
3/28/2012
15
DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
TABLE 2-5
Park-and-Ride Facility Rates: Existing and Proposed
Park-and-Ride
Facility
Alewife
Beachmont
Braintree
Chestnut Hill
Eliot
Forest Hills
Lechmere
Malden
Mattapan*
Milton*
North Quincy
Oak Grove
Orient Heights
Quincy Adams
Quincy Center
Riverside
Suffolk Downs
Sullivan
Waban
Wellington
Wollaston
Woodland
Wonderland
Express Bus**
Commuter Rail**
Route 128***
Ferry**
Existing
$7.00
$5.00
$7.00
$5.50
$5.50
$6.00
$5.50
$5.50
$4.50
$5.00
$5.00
$5.50
$5.00
$7.00
$7.00
$5.75
$5.00
$5.50
$5.50
$5.50
$5.00
$6.00
$5.00
$5.00
$4.00
$5.00
$3.00
Proposed
$7.00
$5.00
$7.00
$6.00
$6.00
$6.00
$6.00
$6.00
$4.00
$4.00
$5.00
$6.00
$5.00
$7.00
$7.00
$6.00
$5.00
$6.00
$6.00
$6.00
$5.00
$6.00
$5.00
$5.00
$4.00
$7.00
$4.00
% Chg.
0.0%
0.0%
0.0%
9.1%
9.1%
0.0%
9.1%
9.1%
-11.1%
-20.0%
0.0%
9.1%
0.0%
0.0%
0.0%
4.3%
0.0%
9.1%
9.1%
9.1%
0.0%
0.0%
0.0%
0.0%
0.0%
40.0%
33.3%
$ Chg.
$0.00
$0.00
$0.00
$0.50
$0.50
$0.00
$0.50
$0.50
-$0.50
$1.00
$0.00
$0.50
$0.00
$0.00
$0.00
$0.25
$0.00
$0.50
$0.50
$0.50
$0.00
$0.00
$0.00
$0.00
$0.00
$2.00
$1.00
* The Mattapan and Milton facilities currently have a $3.00 parking rate, as they are part of the
“Competitive Lots Program,” which investigates lowering the parking rate at underutilized
facilities. The existing rates listed in the table are those that were in place before the
program. This program is intended to terminate on July 1, 2012, and the rates are
programmed to increase to those listed as proposed.
** Park-and-ride daily facility rates are the same for all facilities serving these modes except for
the Route 128 facility. The Fore River Shipyard Ferry Terminal in Quincy also has overnight
and weekly rates that are currently set at $6.00 and $36.00, respectively. These proposed
rates will increase to $8.00 and $48.00, respectively.
*** The park-and-ride rate at the Route 128 facility is currently set at $5.00 for the first 14 hours
and $12.00 for each day thereafter. The post-14 hour rate will increase to $14.00 per day.
The percentage change in prices (Table 2-6) for parking is less than the
percentage changes in single-ride fares and pass prices. This is because parking
rate increases are proposed only for those facilities that are at or above 100
percent utilization. This includes several subway and surface light rail parking
facilities and the Route 128 facility. The zero percent changes for the facilities
with less than 100 percent utilization bring down the percentage changes in the
parking price for subway, surface light rail, and commuter rail as well as for
the overall parking category. Note that the average “fares” (in this case, the
parking rates) for park-and-ride facility modal categories, as in all the other
modal categories, reflect the unlinked-trip price rather than the linked-trip
price.
16
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Boston Region MPO
DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
The largest proposed percentage increases in price (Table 2-6) within a modal
category are generally for CharlieTicket and onboard cash fares. These
increases are greater than the more modest increases in the CharlieCard fares,
due to the greater price increases assessed to CharlieTicket and onboard cash
fares for the local bus, express bus, and rapid transit modes. The increase in
CharlieTicket and onboard cash fares is most apparent when comparing those
fare categories with the CharlieCard with respect to the price for transfers
between local bus and rapid transit service. With a CharlieCard, a “step-up”
transfer between those modes would make the total price for a linked trip
$2.00. The “step-up” transfer benefit is not available on CharlieTickets,
however, resulting in a total proposed linked-trip price of $4.50 using
CharlieTickets or onboard cash.
TABLE 2-6
Weighted Average Percentage Change in Average Fares,
by Modal Category, for Unlinked Trips
Modal Category
Bus
Local Bus
Inner Express
Outer Express
Rapid Transit
Subway
SL Washington
SL Waterfront
Surface Light Rail
Commuter Rail
Zone 1A
Zone 1
Zone 2
Zone 3
Zone 4
Zone 5
Zone 6
Zone 7
Zone 8
Zone 9
InterZone
Onboard
Ferry
F1
F2: Boston
F2: X-Harbor
F2: Logan
Inner Harbor
THE RIDE
ADA Territory
Premium Territory
Parking
Express Bus
Subway
Surface Light Rail
Commuter Rail
Ferry
Total System
CTPS
3/28/2012
% Change
23.9%
23.5%
27.7%
26.4%
19.7%
19.6%
24.7%
20.5%
20.0%
29.2%
19.4%
30.0%
26.1%
30.5%
23.9%
22.9%
25.9%
25.4%
27.4%
26.9%
25.3%
73.1%
43.1%
42.4%
34.6%
30.3%
33.4%
69.8%
100.0%
94.9%
140.0%
1.2%
0.0%
1.1%
3.6%
0.3%
33.3%
22.6%
17
DESCRIPTION OF PROPOSED FARE INCREASE/
SERVICE CHANGE SCENARIO
The percentage increase in pass prices is generally less than that in the
respective single-ride fares. Pass prices increase by various amounts in order to
maintain or revise certain cash-fare equivalents (based on the lowest-priced
respective single-ride fare), which are the number of single-ride trips
equivalent to the total pass price. The difference between the lowest and
highest cash-fare-equivalent values of the various commuter rail passes is
reduced. The cash-fare equivalents of commuter rail passes currently range
from 31.05 to 33.60 trips per pass; under the proposed fare increase in Scenario
3, the cash-fare equivalent would range from 31.33 to 31.50 trips per pass. For
local bus, express bus, and rapid transit passes, the cash-fare equivalent would
decrease or remain virtually the same.
18
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Boston Region MPO
Methods Used to
Estimate Ridership
and Revenue
Two separate approaches were used in this analysis to project the impact of the
proposed fare increase and service reductions on MBTA ridership and revenue.
One approach utilized a set of spreadsheets created by CTPS in consultation
with the MBTA specifically for the purpose of such calculations. The second
approach consisted of applying the Boston Region MPO’s regional travel
demand model set to estimate demand for each MBTA mode using the existing
and proposed fare levels.
The travel demand model set was also employed as a complement to the
spreadsheet model in the 2007 Pre–Fare Increase Impacts Analysis, with the
two models together providing an indication of the potential range of impacts
on ridership and revenue. In addition, unlike the spreadsheet model, the travel
demand model set can also be used to conduct the air quality and
environmental justice impact analyses.
3.1
CTPS SPREADSHEET MODEL APPROACH
The spreadsheet model was used to estimate the revenue and ridership impacts
of the fare increase component of the proposed scenario. This model reflects
the many fare-payment categories of the MBTA pricing system and applies
price elasticities to analyze various changes across these categories. The
accuracy of this methodology was proven to be satisfactory through the 2007
Post–Fare Increase Impacts Analysis, which included an analysis of its
effectiveness in predicting the impacts of the proposed 2007 fare increase.
3.1.1
MODELING OF EXISTING RIDERSHIP AND REVENUE
Inputs to the spreadsheet model included existing ridership in the form of
unlinked trips by mode, by fare-payment method, and by fare-media type. An
unlinked trip is an individual trip on any one transit vehicle; any trip using
multiple vehicles—so-called “linked” trips—is counted as multiple unlinked
trips.
Existing ridership 5 (to which the spreadsheet model applies price elasticity
figures – see Section 3.1.2) for the local bus, express bus, and rapid transit
5
Existing ridership is that for fiscal year 2011 (July 1, 2010–June 30, 2011).
CTPS
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19
METHODS USED TO ESTIMATE RIDERSHIP AND REVENUE
networks was provided in the form of automated fare-collection (AFC) data.
Data were provided by month, with subtotals of transactions (unlinked trips) by
the various possible combinations of product type (single-ride fare or pass) and
stock (smart card, magnetic-stripe ticket, etc.). AFC data were also provided at
the modal level at which each transaction occurs. More detailed information on
AFC fare types, modes, and media can be found in the appendix.
Because AFC equipment has not yet been deployed on commuter rail and
commuter boat, the number of trips on these modes was estimated using sales
figures. Single-ride trips on commuter rail and ferry were set equal to the
number of single-ride fares sold, while pass trips on these modes were
estimated by dividing the number of pass sales by the estimated average
number of trips made using the respective pass type, calculated as part of the
2007 Post–Fare Increase Impacts Analysis. Dividing the number of pass sales
by the estimated number of trips per pass resulted in an estimate of the total
number of pass trips for each pass type.
Other data used were estimates of the number of trips currently made using
THE RIDE and the number of cars currently parked at transit stations. These
data were provided to CTPS directly by the MBTA.
Because the spreadsheet model cannot estimate the ridership impacts of
eliminating or revising service, estimates of the ridership changes that would
be associated with service changes without a fare increase were first calculated
separately in order to adjust the existing ridership numbers to reflect a postservice-change situation. The spreadsheet model then estimated the ridership
and revenue impacts of a fare increase using the revised existing ridership as
the baseline. The MBTA estimated the ridership loss associated with the
service changes and provided those estimates to CTPS.
Revenue for single-ride trips was calculated in the spreadsheet model by
multiplying the number of trips in each fare/modal category by that category’s
price. Revenue for pass trips was calculated for each pass type by multiplying
the number of pass sales by the pass price. Pass revenue was then distributed
between modal categories based on each category’s ridership and weighted by
each category’s single-ride fare.
The calculation of the change in ferry fare revenue collected by the MBTA
presents a special challenge. Currently, the MBTA pays a subsidy to all
contracted ferry operators, who collect and keep all fare revenue. Therefore,
the MBTA does not currently receive any revenue whatsoever from ferry
operations. However, under a new contract that will take effect at the start of
FY 2013, the MBTA will receive the revenue from fare collection. Given this
accounting change, the increase in ferry fare revenue specifically collected by
the MBTA will consist of 100 percent of the existing revenue as well as
whatever additional amount is collected because of the fare increase. However,
this analysis assumed a net ferry revenue change consisting only of the
additional fare revenue resulting from the fare increase.
20
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Boston Region MPO
METHODS USED TO ESTIMATE RIDERSHIP AND REVENUE
3.1.2
ESTIMATION OF RIDERSHIP CHANGES RESULTING FROM A FARE
INCREASE
Fares are one of many factors that influence the level of ridership on transit
services. Price elasticity is the measure of either the expected or observed rate
of change in ridership relative to a change in fares if all other factors remain
constant. On a traditional demand curve that describes the relationship between
price, on the y-axis, and demand, on the x-axis, elasticities are equivalent to the
slope along that curve. As such, price elasticities are generally expected to be
negative, meaning that a price increase will lead to a decrease in demand (with
a price decrease having the opposite effect). The larger the negative value of
the price elasticity (the greater its distance from zero), the greater the projected
impact on demand. Larger (more negative) price elasticities are said to be
relatively “elastic,” while smaller negative values, closer to zero, are said to be
relatively “inelastic.” Thus, if the price elasticity of the demand for transit were
relatively elastic, a given fare increase would cause a greater loss of ridership
than if demand were relatively inelastic. An example of the application of price
elasticities is demonstrated in the appendix.
The spreadsheet model permits the use of various ranges of elasticities to
estimate different possible ridership impacts of price increases. Performing
calculations in the spreadsheet model with the same prices but with a range of
higher and lower elasticities provides a range of estimates. In the present
analysis, the model was generally set to use the middle range of elasticities, as
these represent the best estimate of where the elasticities should be set based on
past experiences. However, estimates were also made using more inelastic and
elastic elasticities, as a sensitivity analysis of the model’s projections of the
ridership losses and revenue gains. Table 3-1 presents the three elasticity
ranges used in the spreadsheet model for this study’s analysis. For a description
of how these elasticity values were determined, see the appendix.
An additional complexity of the spreadsheet model that provides increased
accuracy is its use of ridership diversion factors. These factors reflect estimates
of the likelihood of a switch in demand from one MBTA product type or mode
to another as a result of a change in the relative prices. The diversion factors
essentially work to redistribute demand between the two product types or
modes after the respective price elasticities have been applied. The appendix
provides examples of the application of diversion factors and the methodology
for combining the use of price elasticities and diversion factors. These
examples reflect the methodology used in the present analysis. While diversion
factors estimate the diversion of riders between MBTA product types and
modes based on their price, the spreadsheet model can only estimate the total
loss of riders from the MBTA transit system, not the diversion of riders to
specific non-MBTA modes such as driving or walking.
CTPS
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21
METHODS USED TO ESTIMATE RIDERSHIP AND REVENUE
TABLE 3-1
Price Elasticity Ranges Used in the Spreadsheet Model
Modal Category
Cash Elasticities
Bus
Adult
Senior
Student
Subway
Adult
Senior
Student
Surface Light Rail
Adult
Senior
Student
Commuter Rail
Adult
Half-Fare
Ferry
Adult
Half-Fare
THE RIDE
Parking
Pass Elasticities
Bus
Inner Express
Outer Express
LinkPass
1-Day LinkPass
7-Day LinkPass
Commuter Rail
Ferry
Senior
Student
3.2
Low
Elasticity Range
Medium
High
-0.10
-0.10
-0.05
-0.05
-0.15
-0.15
-0.05
-0.05
-0.15
-0.15
-0.10
-0.10
-0.25
-0.25
-0.15
-0.20
-0.20
-0.10
-0.08
-0.10
-0.20
-0.20
-0.15
-0.15
-0.25
-0.25
-0.15
-0.15
-0.25
-0.25
-0.20
-0.20
-0.35
-0.35
-0.25
-0.30
-0.30
-0.20
-0.12
-0.20
-0.30
-0.30
-0.25
-0.25
-0.35
-0.35
-0.25
-0.25
-0.35
-0.35
-0.30
-0.30
-0.45
-0.45
-0.35
-0.40
-0.40
-0.30
-0.16
-0.30
-0.20
-0.10
-0.10
-0.20
-0.25
-0.25
-0.05
-0.15
-0.05
-0.05
-0.30
-0.20
-0.20
-0.30
-0.35
-0.35
-0.10
-0.25
-0.15
-0.15
-0.40
-0.30
-0.30
-0.40
-0.45
-0.45
-0.20
-0.35
-0.25
-0.25
BOSTON REGION MPO TRAVEL DEMAND MODEL SET
APPROACH
The regional travel demand model set used by CTPS simulates travel on the
transportation network in eastern Massachusetts, including both the transit and
highway systems. It covers all MBTA commuter rail, rapid transit, and bus
services, as well as all private express bus services. The model set reflects
service frequency (how often trains and buses arrive at a given transit stop),
routing, travel time, and fares for all of these services. In the modeling of the
highway system, all express highways, all principal arterial roadways, and
many minor arterial and local roadways are included.
The travel demand forecasting procedure used in this analysis is based on a
traditional four-step, sequential process: trip generation, trip distribution, mode
choice, and trip assignment. This process may be used to estimate average
daily transit ridership, primarily on the basis of estimates of population and
employment, projected highway travel conditions (including downtown
parking costs), and projected transit service to be provided. Such a process was
used to analyze MBTA ridership and revenue impacts due to the proposed fare
22
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Boston Region MPO
METHODS USED TO ESTIMATE RIDERSHIP AND REVENUE
increase and service reductions.
The eastern Massachusetts geographic area represented in the model set is
divided into several hundred areas known as transportation analysis zones
(TAZs). The model set employs sophisticated and complex techniques in each
of the four steps of the process. These steps can be very briefly summarized as
follows.
Trip Generation: This step estimates the number of trips produced in and
attracted to each TAZ. This is done using estimates of the population,
employment, and other socioeconomic and household characteristics of each
zone.
Trip Distribution: This step links the trip ends estimated in the trip generation
step to form zonal trip interchanges (movements between pairs of zones). The
output of this step is a trip table, which is a matrix containing the number of
trips occurring in every origin-zone-to-destination-zone combination.
Mode Choice: This step allocates the person trips estimated in the trip
distribution step to the two primary competing modes, automobile and transit,
and to walking and biking. This allocation is based on the desirability or utility
of each choice a traveler can opt for, based on the attributes of that choice and
the characteristics of the individual. The resulting output of this step includes
the percentage of trips that use automobiles and the percentage that use transit
for all trips that have been generated.
Trip Assignment: This final step assigns the transit trips to the various transit
modes, such as subway, commuter rail, local bus, or express bus. This is done
by assigning each trip to one of several possible transit paths from one zone to
another; each of these assignments is based on minimizing the generalized
“cost” (including not only the transit fare, but also in-vehicle travel time,
number of transfers, etc.). These paths may involve just one mode, such as
express bus or commuter rail, or multiple modes, such as a local bus and a
transfer to the subway. The trip assignment step also assigns the highway trips
to the highway network. Thus, the traffic volumes on the highways and the
ridership on the transit lines can be obtained from the outputs of this step.
Population and employment data are key inputs to the demand forecasting
process; those used in this study were obtained from the Metropolitan Area
Planning Council (MAPC). The highway travel times used in the analysis are
those used in recent CTPS transit and highway studies. Downtown parking
costs were obtained from recent CTPS studies. The travel demand model set
assumes that, in general, people wish to minimize transfers. It also assumes
that they may wish to minimize travel time, even if doing so costs more.
Note that the travel demand model set does not possess the capability of
modeling THE RIDE, given the nature of paratransit service. As a result, the
ridership and revenue impacts on THE RIDE that are included with the travel
demand model set results are taken from the spreadsheet model results.
Existing revenue was estimated by multiplying the trips estimated by the model
CTPS
3/28/2012
23
METHODS USED TO ESTIMATE RIDERSHIP AND REVENUE
set for each mode by the average fare for that mode. The average fares were
based on calculations in the spreadsheet model. The revenue impact was
estimated by taking the ratio from the spreadsheet model of each mode’s
change in revenue divided by the change in unlinked trips and applying this to
the travel demand model set’s estimate of the change in that mode’s unlinked
trips.
3.3
DIFFERENCES BETWEEN THE TWO ESTIMATION
METHODOLOGIES
There are several differences between the two methodologies. The spreadsheet
model is primarily used to estimate the impacts of a fare change (though the
estimated ridership impacts of service changes can be added to the model as an
adjustment to existing ridership, so that the spreadsheet model’s projections
will reflect the impacts of a simultaneous change in fare and service). On the
other hand, the travel demand model set can forecast both impacts caused by
fare changes and those caused by service changes.
The chief strengths of the spreadsheet model are that it accounts for every
distinct type of fare that can be paid for an MBTA transit mode and that it
assigns the fare to the correct number of passengers who are in that farepayment/modal category. In comparison, the travel demand model set does not
permit analysis of fares at this detailed level, but assumes for each moregeneralized modal category an average fare for all fare types. However, unlike
the travel demand model set, the spreadsheet model cannot predict how many
riders who leave the system due to a fare increase are switching to modes other
than transit (driving alone, carpooling, bicycling, or walking). The travel
demand model set also provides the outputs necessary for conducting the air
quality and environmental justice impact analyses.
There is another key difference between the two approaches in how they
estimate ridership changes. The use of elasticities in the spreadsheet model has
a relatively simple premise: the greater the percent change in price, the greater
the percent change in demand. In the travel demand model set, while a greater
percent change in fares will undoubtedly trigger a greater decline in transit
ridership, it is not so much the percent change in transit fares that is important
for determining the overall ridership change. Rather, it is the comparison of the
resulting transit fares to the comparable cost of making the same trip via a
different mode. For example, if the price of transit increases relative to the cost
of driving, the travel demand model set will show transit diversions to driving.
24
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Boston Region MPO
Ridership and
Revenue Impacts
4.1
OVERVIEW OF RESULTS AND METHODOLOGY
Scenario 3 is projected to result in a gain in annual revenue of between $88.3
million using the travel demand model set and $91.6 million using the
spreadsheet model. The corresponding estimated annual ridership losses are
20.2 million and 21.4 million unlinked trips.
The 2007 Post–Fare Increase Impacts Analysis shows the projections from the
spreadsheet model, which uses elasticities to project ridership and revenue
changes based on a detailed analysis by mode and fare category, to be close to
the actual changes in ridership and revenue that occurred after that fare
increase was implemented. In addition, through the 2007 Post–Fare Increase
Impacts Analysis, CTPS was able to adjust the elasticities in the spreadsheet
model to even better reflect the changes that occurred. This presumably
improved the capability of the spreadsheet model to accurately project the
ridership and revenue impacts of other fare increases. However, this marks the
first time that CTPS has modeled the combined impacts of both a fare increase
and service changes. The travel demand model set is capable of incorporating
both a fare increase and service changes into its projections, whereas in the
case of the spreadsheet model, the ridership losses associated with service
changes must be made independently and then added to the model. Therefore,
it was appropriate to use both models in combination as well as to conduct a
sensitivity analysis of the spreadsheet model using different elasticity values to
help to define a range of probable outcomes of the changes in fares and service.
4.2
SPREADSHEET MODEL ESTIMATES
4.2.1
PROJECTIONS
Table 4-1 presents CTPS’s estimates of the ridership and fare revenue impacts
of the Scenario 3 fare increase and service changes produced using the
spreadsheet model and its medium range of elasticities. The existing ridership
and fare revenue numbers, also presented, represent existing conditions before
any adjustments are made to account for the estimated ridership lost due to the
service reductions in this scenario. All figures are annual.
CTPS
3/28/2012
25
RIDERSHIP AND REVENUE IMPACTS
The total projected fare revenue increase from Scenario 3 comes to $76.2
million, or a 15.8 percent increase. The total projected ridership loss is
estimated at 21.4 million annual unlinked trips, or a 5.5 percent decrease. The
greatest absolute fare revenue increase is projected for the commuter rail
category ($28.6 million). This is due partly to the fact that commuter rail not
only has one of the highest existing average fares, but also faces one of the
greater percentage increases in price of all modes. Heavy rail (Blue, Orange,
and Red Lines) has the second-greatest projected absolute revenue increase
($20.1 million), followed by the bus category ($14.5 million). Ferry is
projected to have the greatest percentage decrease in ridership (15.7 percent),
while the absolute number of lost riders is projected to be greatest for heavy
rail (8.1 million unlinked trips).
TABLE 4-1
Spreadsheet Model Estimates of Annual Ridership and Fare Revenue Impacts
Modal Category
Bus
Heavy Rail
Light Rail
Commuter Rail
Ferry
THE RIDE
Parking
Total System
4.2.2
Existing
Fare Revenue
Ridership
$84,943,464 111,903,868
$150,316,826 153,439,900
$61,940,368
77,659,524
$139,408,504
32,808,010
$6,123,737
1,309,167
$3,820,407
2,359,966
$36,501,063
6,889,609
$483,054,370 386,370,044
Fare Revenue Change
$
%
$14,465,569
17.0%
$20,118,742
13.4%
$8,384,386
13.5%
$28,572,633
20.5%
$1,195,195
19.5%
$3,033,136
79.4%
$429,500
1.1%
$76,199,160
15.8%
Ridership Change
#
%
-6,168,961
-5.5%
-8,067,167
-5.3%
-4,143,170
-5.3%
-2,346,821
-7.2%
-204,992
-15.7%
-242,634
-10.3%
-263,279
-3.8%
-21,437,023
-5.5%
SENSITIVITY ANALYSIS
The results reported in Table 4-1 were produced using the medium range of
elasticities. Table 4-2 presents a sensitivity analysis of the spreadsheet model,
showing the range of Scenario 3’s estimated ridership and fare revenue impacts
from the fare increase and service changes using the lower and higher ranges of
elasticities presented in Table 3-1. In the ranges of ridership-loss estimates in
the table, the greater losses are those resulting from the higher range of
elasticities, while in the ranges of fare-revenue-increase estimates, the greater
increases are those resulting from the lower range of elasticities.
The use of the higher range of elasticities results in much greater estimates of
ridership losses: 30.0 million unlinked trips, compared to 13.2 million using
the lower range of elasticities; using the medium range of elasticities results in
a loss of 21.4 million unlinked trips. As a result, the projected revenue gain
from the fare increase estimated using the higher range of elasticities is
approximately $15.0 million less than that estimated using the medium range
of elasticities ($61.2 million versus $76.2 million) and $28.5 million less than
that estimated using the lower range of elasticities.
26
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Boston Region MPO
RIDERSHIP AND REVENUE IMPACTS
TABLE 4-2
Spreadsheet Model Ranges of Estimates of Annual Ridership and Fare Revenue Impacts
Using Low and High Ranges of Elasticities
Range of Fare Revenue Increases
$ Range
$ (millions)
%
(millions)
$11.9─$17.0
14.0%─20.0%
$5.1
$16.4─$23.7
10.9%─15.8%
$7.3
$6.9─$9.9
11.1%─16.0%
$3.0
$22.6─$33.3
16.2%─23.9%
$10.6
$0.9─$1.5
13.9%─25.0%
$0.7
$2.7─$3.4
70.6%─88.2%
$0.7
($0.2)─$0.9
(0.5%)─2.5%
$1.1
$61.2─$89.7
12.7%─18.6%
$28.5
Modal Category
Bus
Heavy Rail
Light Rail
Commuter Rail
Ferry
THE RIDE
Parking
Total System
4.2.3
Range of Ridership Losses
#
# Range
%
(millions)
(millions)
3.6─8.8
3.2%─7.9%
5.2
5.0─11.3
3.2%─7.3%
6.3
2.5─5.8
3.3%─7.4%
3.2
1.7─3.2
5.1%─9.9%
1.6
0.2─0.3 11.8%─19.6%
0.1
0.2─0.3
6.9%─13.7%
0.2
0.2─0.4
2.6%─5.4%
0.2
13.2─30.0
3.4%─7.8%
16.8
TOTAL REVENUE ESTIMATE
Table 4-3 adds the MBTA’s estimates of saved operating costs 6 from Scenario
3’s service changes to the spreadsheet model’s estimates of the gains in fare
revenue from Scenario 3’s fare increase and service changes reported in Table
4-1 to obtain an estimate of the change in total revenue. Commuter rail again
represents the greatest revenue gain, as the saved operating costs on this mode
place its total revenue gain even further above that of heavy rail, which is the
only mode not affected by the proposed service changes.
TABLE 4-3
Spreadsheet Model Estimates of Total Revenue Change:
Combined Fare Revenue Gains and Saved Operating Costs
Modal Category
Fare Revenue Gain
Bus
Heavy Rail
Light Rail
Commuter Rail
Ferry
THE RIDE
Parking
Total System
Saved Operating Costs
$14,465,569
$20,118,742
$8,384,386
$28,572,633
$1,195,195
$3,033,136
$429,500
$76,199,160
$2,496,578
$0
$301,625
$2,816,871
$174,900
$9,609,692
$0
$15,399,665
Fare Revenue Gain +
Saved Operating Costs
$16,962,147
$20,118,742
$8,686,010
$31,389,504
$1,370,095
$12,642,827
$429,500
$91,598,825
4.3
REGIONAL TRAVEL DEMAND MODEL SET ESTIMATES
4.3.1
PROJECTIONS
Table 4-4 presents CTPS’s estimates, produced using the travel demand model
set, of the ridership and fare revenue impacts of the fare increase and service
changes proposed in Scenario 3. All figures are annual. The travel demand
model set projects that the greatest absolute increase in fare revenue will occur
6
The MBTA’s method for estimating saved operating costs for all modes except THE RIDE was based on
the projected decrease in vehicle revenue hours from the service changes. To calculate saved operating
costs for THE RIDE, the change in ridership for ADA-territory and premium-territory trips was estimated
using the CTPS spreadsheet model. This projected ridership loss was multiplied by the estimated net cost
per trip to calculate the saved operating costs for each fare category of THE RIDE.
CTPS
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RIDERSHIP AND REVENUE IMPACTS
on heavy rail. The greatest percentage increase aside from THE RIDE 7 is also
projected for heavy rail, though this increase is only slightly greater than the
increases for light rail and commuter rail. These projected impacts reflect the
fact that no service changes are proposed for heavy rail and service changes
affecting only a small percentage of riders are proposed for light rail and
commuter rail. In terms of ridership, the greatest projected absolute decrease is
estimated on the bus mode because several bus routes either are eliminated or
have a routing revision or frequency reduction. The greatest percentage
decreases in ridership are on ferry and commuter rail. This is likely caused by a
more elastic response to the fare increase given the already high ferry and
commuter rail fares and pass prices and by the diversion of ferry and commuter
rail riders to the less expensive heavy rail and light rail modes; that diversion
somewhat lessens the ridership decreases on heavy and light rail.
TABLE 4-4
Travel Demand Model Set Estimates of Annual Ridership and Fare Revenue Impacts
Existing
Fare Revenue
Ridership
$84,943,464 111,903,868
$150,316,826 153,439,900
$61,940,368
77,659,524
$139,408,504
32,808,010
$6,123,737
1,309,167
$3,820,407
2,359,966
$36,501,063
6,889,609
$483,054,370 386,370,044
Modal Category
Bus
Heavy Rail
Light Rail
Commuter Rail
Ferry
THE RIDE
Parking
Total System
4.3.2
Fare Revenue Change
$
%
$9,876,057
11.6%
$26,162,279
17.4%
$10,416,645
16.8%
$21,941,988
15.7%
$411,863
6.7%
$3,033,136
79.4%
$1,097,354
3.0%
$72,939,320
15.1%
Ridership Change
#
%
-11,075,868
-9.9%
-2,899,900
-1.9%
-1,999,524
-2.6%
-3,558,010
-10.8%
-323,167
-24.7%
-242,634
-10.3%
-139,609
-2.0%
-20,238,712
-5.2%
TOTAL REVENUE ESTIMATE
Table 4-5 adds the MBTA’s estimates of saved operating costs from Scenario
3’s service changes to the travel demand model set’s estimates of the changes
in fare revenue resulting from Scenario 3’s fare increase and service
reductions. Under this scenario, while heavy rail has the greatest revenue gain,
the saved operating costs for the bus and commuter rail modes place their total
revenue gain closer to that of heavy rail, which only incurs a fare increase.
TABLE 4-5
Travel Demand Model Set Estimates of Total Revenue Change:
Combined Fare Revenue Gains and Saved Operating Costs
Modal Category
Bus
Heavy Rail
Light Rail
Commuter Rail
Ferry
THE RIDE
Parking
Total System
Fare Revenue Gain
Saved Operating Costs
$9,876,057
$26,162,279
$10,416,645
$21,941,988
$411,863
$3,033,136
$1,097,354
$72,939,320
$2,496,578
$0
$301,625
$2,816,871
$174,900
$9,609,692
$0
$15,399,665
Fare Revenue Gain +
Saved Operating Costs
$12,372,634
$26,162,279
$10,718,270
$24,758,859
$586,763
$12,642,827
$1,097,354
$88,338,985
7
The travel demand model set does not include inputs for modeling THE RIDE. Therefore, trips on THE
RIDE are set equal to those estimated using the spreadsheet model.
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RIDERSHIP AND REVENUE IMPACTS
4.4
COMPARISON OF MODEL RESULTS: RANGES OF
PROJECTED IMPACTS
Projected ranges of ridership impacts and fare revenue impacts of the proposed
Scenario 3 fare increase and service changes are presented, respectively, in
Tables 4-6 and 4-7. Probable ranges of impacts have been projected, as
discussed above, by using both the spreadsheet model and the travel demand
model set. As can be seen, the projections from the travel demand model set
show a smaller overall decrease in ridership and a smaller overall increase in
fare revenue than are projected using the spreadsheet model (with mediumrange elasticities).
Using the travel demand model set, CTPS projects a decrease of 20.2 million
unlinked trips, or a 5.2 percent decrease, compared to a decrease of 21.4
million unlinked trips, or a 5.5 percent decrease, using the spreadsheet model.
The projections from the travel demand model set show smaller ridership
decreases in the heavy rail and light rail modal categories and larger ridership
decreases in the bus, commuter rail, and ferry categories compared to the
spreadsheet model.
While the travel demand model set appears to estimate a less elastic response
of riders overall to the fare increase than the spreadsheet model, the differences
in heavy rail and light rail estimates may be caused by a combination of
factors. It appears that, in addition to generally projecting a less elastic
response, the travel demand model set is also estimating that a significant
number of commuter rail riders will divert to heavy and light rail. This
diversion occurs to a greater extent on commuter rail than other modes because
its cost is already high, and the fare increase brings prices to a level where
riders will search for less expensive travel options. The proposed elimination
of weekend service on several commuter rail lines would also encourage some
riders to switch to heavy and light rail at those times when commuter rail is no
longer in service. In addition, the decline in commuter rail ridership is likely
contributed to by a number of riders switching to the automobile mode as the
already high cost of commuter rail makes driving relatively more competitive
with commuter rail than it is for users of other transit modes. Some of the same
factors are likely causing the travel demand model set’s projections of a greater
ferry ridership decrease than that projected using the spreadsheet model.
In terms of annual fare revenue, projections from the travel demand model set
show a gain of $72.9 million, or a 15.1 percent increase, compared to a gain of
$76.2 million, or a 15.8 percent increase, from the spreadsheet model. When
comparing modes, the smaller estimates of ridership loss from the travel
demand model set for heavy and light rail result in greater estimates of fare
revenue gains for these modes compared to the spreadsheet model. Conversely,
the greater ridership losses estimated by the travel demand model set for bus,
commuter rail, and ferry are correlated with smaller estimated fare revenue
gains for these modes compared to the spreadsheet model. As was the case in
the ridership projections, it appears that these differences between the models’
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RIDERSHIP AND REVENUE IMPACTS
estimates can be at least partly explained by the travel demand model set’s
projected diversion of commuter rail and ferry riders to heavy and light rail.
Overall, this diversion would represent a loss in fare revenue, as riders switch
from the higher-priced mode to lower-priced modes. Indeed, the smaller
revenue gains projected by the travel demand model set for commuter rail and
ferry result in the travel demand model set’s overall projection of total fare
revenue being less than that of the spreadsheet model.
Taken together, the projections shown in these tables provide a probable range
of outcomes from the proposed fare increase and service changes in terms of
ridership and fare revenue impacts.
TABLE 4-6
Range of Ridership Projections
Modal Category
Bus
Heavy Rail
Light Rail
Commuter Rail
Ferry
THE RIDE
Parking
Total System
Existing
111.9M
153.4M
77.7M
32.8M
1.3M
2.4M
6.9M
386.4M
Annual Ridership
Spreadsheet Model
Travel Demand Model Set
Projected
# Chg. % Chg.
Projected
# Chg. % Chg.
105.7M
-6.2M
-5.5%
100.8M
-11.1M
-9.9%
145.4M
-8.1M
-5.3%
150.5M
-2.9M
-1.9%
73.5M
-4.1M
-5.3%
75.7M
-2.0M
-2.6%
30.5M
-2.3M
-7.2%
29.3M
-3.6M -10.8%
1.1M
-0.2M -15.7%
1.0M
-0.3M -24.7%
2.1M
-0.2M -10.3%
2.1M
-0.2M -10.3%
6.6M
-0.3M
-3.8%
6.8M
-0.1M
-2.0%
364.9M
-21.4M
-5.5%
366.1M
-20.2M
-5.2%
TABLE 4-7
Range of Fare Revenue Projections
Mode
Bus
Heavy Rail
Light Rail
Commuter Rail
Ferry
THE RIDE
Parking
Total System
Existing
$84.9M
$150.3M
$61.9M
$139.4M
$6.1M
$3.8M
$36.5M
$483.1M
Annual Fare Revenue
Spreadsheet Model
Travel Demand Model Set
Projected
$ Chg. % Chg.
Projected
$ Chg. % Chg.
$99.4M +$14.5M +17.0%
$94.8M +$9.9M +11.6%
$170.4M +$20.1M +13.4%
$176.5M +$26.2M +17.4%
$70.3M +$8.4M +13.5%
$72.4M +$10.4M +16.8%
$168.0M +$28.6M +20.5%
$161.4M +$21.9M +15.7%
$7.3M +$1.2M +19.5%
$6.5M +$0.4M +6.7%
$6.9M +$3.0M +79.4%
$6.9M +$3.0M +79.4%
$36.9M +$0.4M +1.2%
$37.6M +$1.1M +3.0%
$559.3M +$76.2M +15.8%
$556.0M +$72.9M +15.1%
Table 4-8 adds the projected saved operating costs from service changes to the
two models’ estimates of the revenue change from the fare increase. Therefore,
this table presents a range of projections for the total estimated revenue change
resulting from Scenario 3. The total change in revenue is projected to be an
increase ranging between $88.3 million and $91.6 million, or between an 18.3
percent and a 19.0 percent increase.
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Boston Region MPO
RIDERSHIP AND REVENUE IMPACTS
TABLE 4-8
Range of Projections for Total Revenue:
Combined Fare Revenue Gains and Saved Operating Costs
Mode
Bus
Heavy Rail
Light Rail
Commuter Rail
Ferry
THE RIDE
Parking
Total System
CTPS
Existing
$84.9M
$150.3M
$61.9M
$139.4M
$6.1M
$3.8M
$36.5M
$483.1M
Annual Total Revenue
Spreadsheet Model
Travel Demand Model Set
Projected
$ Chg. % Chg.
Projected
$ Chg. % Chg.
$101.9M +$17.0M +20.0%
$97.3M +$12.4M +14.6%
$170.4M +$20.1M +13.4%
$176.5M +$26.2M +17.4%
$70.6M +$8.7M +14.0%
$72.7M +$10.7M +17.3%
$170.8M +$31.4M +22.5%
$164.2M +$24.8M +17.8%
$7.5M +$1.4M +22.4%
$6.7M +$0.6M +9.6%
$16.5M +$12.6M +330.9%
$16.5M +$12.6M +330.9%
$36.9M
$0.4M +1.2%
$37.6M
$1.1M +3.0%
$574.7M +$91.6M +19.0%
$571.4M +$88.3M +18.3%
3/28/2012
31
Air Quality Impacts
5.1
BACKGROUND
The air quality impacts of alternative transportation scenarios can be analyzed
using standard transportation-forecasting models, including the Boston Region
MPO’s travel demand model set. The travel demand model set can be used to
estimate future traffic characteristics within the region’s transportation
network: traffic volumes, average highway speeds, and vehicle-miles and
vehicle-hours traveled. Since the amount of air pollution emitted by highway
traffic depends on the prevailing highway speeds and vehicle-miles traveled, it
is possible to estimate these air quality impacts with reasonable accuracy.
Air pollutants produced by vehicles generally fall into two groups: gaseous and
particulate. Examples of gaseous pollutants include carbon monoxide (CO),
volatile organic compounds (VOC, also known as hydrocarbons), nitrogen
oxides (NOx), and carbon dioxide (CO2). In addition, there are the
photochemical oxidants (such as ozone), which are not directly emitted from
vehicles but are formed when VOC and NOx chemically react in the presence
of sunlight and warm temperatures. Particulate pollutants produced by vehicles
are commonly broken into two categories: fine particulates—those with a
diameter of 2.5 micrometers or less, and coarse particulates—those with a
diameter between 2.5 and 10 micrometers.
Under the Clean Air Act, the U.S. Environmental Protection Agency (EPA)
sets standards for various types of emissions. Historically, EPA has regulated
particulates, CO, and ground-level ozone, all of which are hazardous to human
health. The Boston Region MPO is currently required to report the amount of
CO, NOx, and VOC produced by the regional transportation system in such
documents as the Transportation Improvement Program and the Long-Range
Transportation Plan. Due to its contribution to climate change, CO2 is also an
important type of emission to measure.
CTPS employs EPA MOBILE 6.2 emission factors for calculating the amounts
of pollutants. For each link within the highway network, the travel demand
model set applies the MOBILE 6.2 emission factors corresponding to the link’s
average speed and estimates the emissions of pollutants based on the vehiclemiles traveled on that link. The total amount of emissions of a pollutant in the
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AIR QUALITY IMPACTS
entire region is obtained by summing the amounts associated with the
individual links in the system.
5.2
ESTIMATED AIR QUALITY IMPACTS
With respect to the fare increase and service changes proposed in Scenario 3,
the air quality impacts are primarily those associated with existing transit users
who choose to drive to their destinations instead of using transit. A reduction in
transit trips and addition of automobile trips generally causes increases in the
generation of CO, VOC, NOx, CO2, and particulates, and these increases can
be measured in the manner described in the preceding section. It should be
noted that as the numbers of automobile trips and vehicle hours increase, the
congestion on area roadways also increases. This additional congestion results
in lower travel speeds (which are associated with higher emissions of
pollutants) for all vehicles, not just those of former transit users. While air
quality will typically worsen in response to fare increases and service
reductions, the elimination of transit vehicle trips does represent a reduction in
emissions, and this reduction is included in the estimates produced using the
travel demand model set.
After calculating the ridership impacts as described earlier in this report, CTPS
used the model set to estimate the change in regional vehicle-miles traveled
and average miles per hour for private automobiles and transit vehicles.
Specifically, for automobiles, the path of each automobile trip made by a
former transit user was identified and the travel times for all automobile trips
were estimated. For transit vehicles, the paths and travel times for all
eliminated trips were identified. CTPS applied to these data the emission
factors provided by the EPA that are associated with each of the pollutants
identified above.
As shown in Table 5-1, automobile vehicle-miles and vehicle-hours traveled
are estimated to increase and average miles per hour is estimated to decrease
because of the proposed fare increase and service changes. Transit vehiclemiles traveled are also estimated to decrease. The projected regional change in
emissions per weekday of each of the selected pollutants is reported for the
sum of automobile and transit emissions.
Scenario 3 results in increases in all pollutant emissions and an overall
worsening of air quality. VOC emissions increase by the greatest percentage,
followed by CO and CO2. Scenario 3 bears out a general rule that usually
applies in air quality analyses of this kind: any loss in transit ridership that
results in an increase in auto vehicle-miles and vehicle-hours traveled will lead
to some level of increase in pollutants.
34
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Boston Region MPO
AIR QUALITY IMPACTS
TABLE 5-1
Projected Average Weekday Changes in Selected Pollutants (Regionwide)
Indicator/Pollutant
Auto vehicle-miles traveled
Auto vehicle-hours traveled
Auto average miles-per-hour
Transit vehicle-miles traveled
Carbon monoxide (kg)
Nitrogen oxides (kg)
Volatile organic compounds (kg)
Carbon dioxide (kg)
Fine particulates (kg)
Coarse particulates (kg)
CTPS
3/28/2012
Absolute
Change
+289,244
+17,491
-0.09
-1,750
+3,464
+266
+162
+157,548
+7
+11
Percent
Change
+0.28%
+0.55%
-0.27%
-1.51%
+0.28%
+0.19%
+0.38%
+0.27%
+0.20%
+0.22%
35
Environmental
Justice Impacts
6.1
DEFINITION OF ENVIRONMENTAL JUSTICE COMMUNITIES
To assess the impacts of Scenario 3’s proposed fare increase and service
changes on minority and low-income communities, CTPS conducted an
environmental justice (EJ) impacts analysis. Environmental justice
communities were identified based on a methodology developed from the
MBTA’s ongoing Title VI program and on past practice of CTPS. For the
purposes of Title VI analyses, the MBTA has defined two service areas with
different demographic characteristics: one for the urban fixed-route transit
system and another for the commuter rail system. Therefore, the Authority has
two sets of criteria for identifying EJ communities, one for each service area.
For each of the two service areas, the average annual income and the
percentage of minority population were identified for each transportation
analysis zone (TAZ). A TAZ was then defined as low-income if its income
level was at or below 60 percent of the median household income in the service
area; this meant at or below $40,766 in the urban fixed-route transit service
area and $41,636 in the commuter rail service area. 8 Minority TAZs were
defined as those in which the percentage of the non-white population
(including the Hispanic population) was greater than the average for the service
area. The average percentage of minority residents is 31.3 percent in the urban
fixed-route transit service area and 26.2 percent in the commuter rail service
area. Any TAZ which qualifies as minority and/or low-income is considered an
EJ community.
6.2
EQUITY DETERMINATION
After identifying the EJ communities in both service areas, CTPS analyzed, for
each service area (except where noted otherwise), areawide equity in terms of
both the existing and proposed conditions for Scenario 3 using the Boston
Region MPO’s travel demand model set. Each TAZ’s “score” in terms of
various metrics was estimated by the model set for both the existing system
and each projected scenario. To measure the areawide results, averages across
8
Median household income was determined based on the 2006-2010 American Community Survey.
Minority percentages were determined based on the 2010 U.S. Census.
CTPS
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37
ENVIRONMENTAL JUSTICE IMPACTS
TAZs (for EJ and non-EJ communities) were calculated; in this calculation,
each TAZ’s score was weighted according to its existing transit trips. The
statistical significance of the difference between the EJ and non-EJ averages
was also calculated.
Three general categories of metrics were analyzed with respect to their
projected equity impacts. Note that this analysis used data for the weekday AM
peak time period, as this represents the greatest number of transit trips in any
time period.
For the first category, transit equity, the measures were the average fare, the
average walk-access time, the average wait time, the average in-vehicle travel
time, the average number of transfers, and the total number of transit trips. All
averages were weighted by the number of trips originating from each TAZ (as
opposed to the trips destined for each TAZ).
The second category was highway congestion and air quality. Average vehiclemiles traveled per square mile was the metric for representing local levels of
congestion. Average carbon monoxide emissions per square mile was the
metric representing the local level of air pollution (since carbon monoxide is a
local pollutant).
The third category was accessibility. The travel demand model set was utilized
to produce measures of transit accessibility to various types of destinations;
accessibility was measured relative to the ability to access the desired
destination by transit within at least 40 minutes, which is based on the average
commute trip time for the Boston region. Jobs were one of the destination
types included in the measurement of transit accessibility; specifically, service
sector jobs were used in this analysis, as the results tended to mirror those for
the other job sectors. Accessibility to healthcare (as measured by the total
number of beds at the accessible health facilities) and accessibility to postsecondary education (as measured by the total enrollment at the accessible
colleges) were also measured by the travel demand model set.
6.2.1
TRANSIT EQUITY METRICS
Table 6-1 presents the existing and projected values for the six transit equity
metrics: average fare ($ per trip), average walk-access time (minutes), average
wait time (minutes), average in-vehicle travel time (minutes), average number
of transfers, and total number of transit trips. As seen in the tables, in both the
commuter rail and urban fixed-route service areas, the existing average fare is
less for EJ communities than for non-EJ communities, as are the average walkaccess time, wait time, and in-vehicle travel time. This reflects the greater
concentration of EJ communities in areas currently well-served by transit,
which also tend to be more urban and densely developed. For these same
reasons, EJ communities have more than 1.68 and 1.90 times the number of
transit trips compared to non-EJ communities in the commuter rail and urban
fixed-route service areas, respectively. These relationships between the EJ and
non-EJ existing conditions remain consistent in the projected conditions.
38
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Boston Region MPO
ENVIRONMENTAL JUSTICE IMPACTS
In both areas, the absolute increase in average fare is slightly less for EJ
communities than non-EJ communities. This likely reflects the greater fare
increase on modes that are generally located outside the urban core, such as
commuter rail and ferry. As a percentage change, in the commuter rail service
area, the increase in average fare is less for EJ communities than non-EJ
communities; however, in the urban fixed-route service area, since the existing
average fare for EJ communities is lower than the non-EJ average, the nearly
equal absolute price increase affects EJ communities relatively more on a
percentage basis. The percentage increases for both service areas in average
walk-access time, wait time, in-vehicle travel time, and number of transfers are
all slightly greater for non-EJ communities compared to EJ communities.
Although the changes in all existing and projected measures appear to be
statistically significant for both EJ and non-EJ communities, the differences
between EJ and non-EJ communities in the amounts of change are so minimal
for several measures that they fail to be statistically significant, indicating that
there would be no perceptible difference between the changes in these
measures for EJ and those for non-EJ communities. Finally, both the absolute
and percentage decreases in transit trips in Scenario 3 are greater for non-EJ
communities than EJ communities.
6.2.2
HIGHWAY CONGESTION AND AIR QUALITY EQUITY METRICS
Table 6-2 presents the existing and projected measures of average vehiclemiles traveled (VMT) per square mile and average kilograms of carbon
monoxide (CO) emissions per square mile. The first metric was used to
represent impacts on local congestion, and the second was used to represent
impacts on local air pollution.
As shown in the table, the average existing-conditions measures of both VMT
and CO emissions are greater for EJ communities than non-EJ communities.
This is a reflection of the much greater traffic levels in the more urban areas,
which is where EJ communities are typically located. In both the urban fixedroute and commuter rail service areas, EJ communities have existing averages
for VMT and average CO per square mile that are nearly three times the
averages for non-EJ communities.
Unlike the transit equity metrics, the highway congestion and air quality
metrics show a greater negative impact on EJ communities compared to non-EJ
communities, an exacerbation of the difference in local congestion and air
quality that already exists. These differences in the percentage changes
between EJ and non-EJ communities were determined to be statistically
significant. The absolute increase in the average VMT per square mile for EJ
communities is more than six times that for non-EJ communities for both the
commuter rail and urban fixed-route service areas, and the absolute increase in
the average CO per square mile for EJ communities is nearly seven times that
for non-EJ communities for the commuter rail service area and more than
seven times that for non-EJ communities in the urban fixed-route service area.
The differences between existing and projected measures for both EJ and non-
CTPS
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39
ENVIRONMENTAL JUSTICE IMPACTS
EJ communities are also statistically significant.
6.2.3
ACCESSIBILITY EQUITY METRICS
Table 6-3 presents the existing and projected accessibility measures. Access to
jobs is measured by the number of jobs in the service employment category
that can be accessed by transit. The changes in accessibility to service jobs
largely match those for retail and other jobs; therefore, service jobs are
presented in the table as a proxy for all jobs. Access to healthcare is measured
by the number of hospitals, weighted by hospital beds, that can be accessed by
transit. Access to higher education is measured by the two- and four-year
institutions, weighted by enrollment, that can be accessed by transit. These
metrics indicate the accessibility of high-demand destinations from EJ and
non-EJ communities.
As seen in the table, in both the commuter rail and urban fixed-route service
areas, EJ communities have a greater level of existing access in terms of all
three metrics compared to non-EJ communities. This basic difference between
EJ and non-EJ accessibility is not projected to change in Scenario 3. Indeed,
the absolute and percentage changes in accessibility are slightly worse for nonEJ communities than EJ communities. However, none of the differences
between the changes for EJ and those for non-EJ communities are statistically
significant, indicating that there would be no perceptible difference between
the EJ and non-EJ communities in terms of their changes in measures. For each
of the accessibility measures, the difference between existing and projected is
statistically significant for only either EJ or non-EJ communities, but not both.
6.2.4
SUMMARY OF EQUITY IMPACTS
In general, for the metrics in which EJ communities have better existing
“scores” than non-EJ communities, that is, for the transit and accessibility
equity measures, Scenario 3, while making the scores slightly worse overall,
degrades the scores less for EJ versus non-EJ communities. For example, the
existing EJ average fare is less than the non-EJ average fare, and Scenario 3
results in a greater absolute increase in the non-EJ average fare, further
increasing the difference. For the metrics in which EJ communities have worse
existing scores than non-EJ communities, that is, for the highway congestion
and air quality equity measures, Scenario 3 results in larger negative impacts
on EJ communities than non-EJ communities, again further increasing the
differences. The differences between EJ and non-EJ communities for several of
the various measures are so small (less than one percent) that they fail to be
statistically significant, indicating that there would be no perceptible
difference.
40
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Boston Region MPO
TABLE 6-1
Existing and Projected Measures of Transit Equity Metrics
Existing
Projected
Absolute Change
Percentage Change
Metric*
EJ
Non-EJ
EJ
Non-EJ
EJ
Non-EJ
EJ
Non-EJ
Average Fare4
$2.11
$2.20
$2.52
$2.64
+$0.41
+$0.45
+19.3%
+20.4%
Walk-Access Time (min.)2,3
19.35
20.97
19.38
21.00
+0.03
+0.03
+0.1%
+0.2%
Wait Time (min.)1,2,3
16.79
18.10
16.91
18.25
+0.12
+0.15
+0.7%
+0.8%
In-Vehicle Time (min.)2,3
47.06
52.48
47.11
52.56
+0.05
+0.08
+0.1%
+0.2%
Number of Transfers1,2,3
1.75
1.75
1.75
1.76
<0.01
+0.01
+0.3%
+0.4%
Total Transit Trips4
142,205
84,652
139,273
80,410
-2,932
-4,211
-2.1%
-5.0%
4
Urban Fixed-Route Average Fare
$2.00
$2.25
$2.41
$2.68
+$0.41
+$0.42
+20.2%
+18.8%
Walk-Access Time (min.)2,3
19.34
20.63
19.37
20.66
+0.03
+0.04
+0.1%
+0.2%
Wait Time (min.)1,2,3
16.83
17.76
16.96
17.90
+0.12
0.14
+0.7%
+0.8%
In-Vehicle Time (min.)2,3
47.08
51.29
47.14
51.35
+0.06
+0.06
+0.1%
+0.1%
Number of Transfers1,2,3
1.76
1.74
1.76
1.74
<0.01
+0.01
+0.3%
+0.4%
Total Transit Trips4
135,296
71,209
132,729
68,300
-2,567
-2,909
-1.9%
-4.1%
* For measures without a note, there are no statistically significant differences either between the EJ and non-EJ changes or between the existing and projected
values for either EJ or non-EJ communities.
1
Indicates that the difference between the EJ change and the non-EJ change is statistically significant.
2
Indicates that the difference between the existing and projected values for EJ communities is statistically significant.
3
Indicates that the difference between the existing and projected values for non-EJ communities is statistically significant.
4
No statistical test was performed for average fare or total transit trips, since neither of these measures has a distribution to which a statistical test could be
applied. Average fare equals the total trip cost factored to eliminate the parking cost, but this factoring is performed after the weighted average of the total trip
cost is calculated based on the distribution of total trip costs by TAZ, not at the individual TAZ level. Transit trips are a total and do not have a distribution of
values.
Service Area
Commuter Rail
TABLE 6-2
Existing and Projected Measures of Highway Congestion and Air Quality Equity Metrics
Existing
Projected
Absolute Change
Percentage Change
Metric*
EJ
Non-EJ
EJ
Non-EJ
EJ
Non-EJ
EJ
Non-EJ
Avg. VMT / Sq. Mile1,2,3
38,406
13,822
38,686
13,867
+280
+45
+0.7%
+0.3%
Avg. CO / Sq. Mile (g)1,2,3
457,390
164,821
460,954
165,352
+3,564
+531
+0.8%
+0.3%
1,2,3
Urban Fixed-Route Avg. VMT / Sq. Mile
40,805
14,280
41,119
14,329
+314
+49
+0.8%
+0.3%
Avg. CO / Sq. Mile (g)1,2,3
486,655
170,224
490,693
170,798
+4,039
+574
+0.8%
+0.3%
* For measures without a note, there are no statistically significant differences either between the EJ and non-EJ changes or between the existing and projected
values for either EJ or non-EJ communities.
1
Indicates that the difference between the EJ change and the non-EJ change is statistically significant.
2
Indicates that the difference between the existing and projected values for EJ communities is statistically significant.
3
Indicates that the difference between the existing and projected values for non-EJ communities is statistically significant.
Service Area
Commuter Rail
CTPS
3/28/2012
41
TABLE 6-3
Existing and Projected Measures of Accessibility Equity Metrics
Existing
Projected
Absolute Change
Percentage Change
Metric*
EJ
Non-EJ
EJ
Non-EJ
EJ
Non-EJ
EJ
Non-EJ
Service Jobs2
291,728
193,024
290,678
191,880
-1,051
-1,143
-0.4%
-0.6%
Hospital Beds3
3,059
2,021
3,043
2,006
-15
-15
-0.5%
-0.7%
College Enrollment3
45,594
33,996
45,601
33,745
+6
-251
<0.1%
-0.7%
2
Urban Fixed-Route Service Jobs
290,825
215,530
289,888
214,239
-937
-1,291
-0.3%
-0.6%
Hospital Beds3
3,049
2,258
3,033
2,245
-16
-13
-0.5%
-0.6%
College Enrollment3
44,687
37,821
44,711
37,600
+24
-221
+0.1%
-0.6%
* For measures without a note, there are no statistically significant differences either between the EJ and non-EJ changes or between the existing and projected
values for either EJ or non-EJ communities.
1
Indicates that the difference between the EJ change and the non-EJ change is statistically significant.
2
Indicates that the difference between the existing and projected values for EJ communities is statistically significant.
3
Indicates that the difference between the existing and projected values for non-EJ communities is statistically significant.
Service Area
Commuter Rail
42
3/28/2012
Boston Region MPO
Conclusions
The means available to the MBTA for addressing the $161 million projected
budget deficit for FY 2013 are limited to increasing fares and reducing service,
although the MBTA will continue to advance the operational and
administrative efficiencies undertaken since the implementation of forward
funding in 2000 and transportation reform in 2009. Two proposed scenarios
that combine those two means in different ways to fully close the budget gap
are described in a separate report. Scenario 3, the proposal analyzed in this
report, also raises revenue through both a fare increase and service reductions,
but the changes are smaller than those in Scenarios 1 and 2. Consequently,
Scenario 3 does not close the entire FY 2013 budget gap, but is projected to
result in an increase in revenue of between $88.3 million and $91.6 million.
This scenario, which was developed after the MBTA had received significant
public input in response to Scenarios 1 and 2, is now feasible, as MassDOT has
identified additional funding sources that will meet the remainder of the
MBTA’s FY 2013 budget deficit.
Closing the budget deficit employing only a fare increase or only service
reductions is untenable. Modeling exercises done with the spreadsheet model
show that it is not feasible to increase fares to an extent that would raise $161
million: the ridership losses estimated to result are so substantial under any fare
increase above 60 percent that the fare revenue increases become minimal.
Similarly, cutting $161 million from operating expenses is also infeasible, as
the necessary service reductions would likely reduce ridership to such an extent
that the already low average revenue per passenger would decrease even
further.
While the previously proposed Scenarios 1 and 2 are projected to produce
roughly equivalent gains in revenue, and either would close the projected
budget deficit, both scenarios would impose a significant burden on MBTA
riders in terms of increased prices and eliminated services. The concept behind
Scenario 3 is that it is not feasible for transit riders to shoulder the entire
burden of closing the budget gap. Therefore, the percentage magnitude of the
fare increase proposed in Scenario 3 is more in line with previous fare
increases, and service changes are only proposed for those routes that have the
worst cost efficiency in the entire MBTA system or the change to which would
CTPS
3/28/2012
43
CONCLUSIONS
only affect a small percentage of passengers. Again, however, Scenario 3
cannot close the entire FY 2013 budget gap by itself; MassDOT has identified
additional funding sources. In addition, while this scenario does marginally
reduce the systemwide net cost per passenger, in the long run it does not
change the situation currently faced by the MBTA, namely, operating too many
services that cost too much money given the size of the MBTA’s dedicated
revenue stream.
Neither fare increases nor service reductions present an appealing choice, but
the primary methods that the MBTA has at its disposal for reducing deficits are
these two measures, barring any additional sources of revenue. This report’s
projections of the impacts of Scenario 3 on ridership, revenue, air quality, and
environmental justice communities will inform the Authority’s decision
making. It is based on these data—and on a vision of what shape the MBTA
will take in the future—that a course of action must be chosen.
44
3/28/2012
Boston Region MPO
APPENDIX
Spreadsheet Model Methodology
A.1
APPORTIONMENT OF EXISTING RIDERSHIP
Automated fare-collection (AFC) data are provided on a monthly basis,
including subtotals of transactions (unlinked trips) for the various combinations
of fare type, fare mode, and fare media (Table A-1).
TABLE A-1
AFC Fare Categories
Fare Type
Fare Mode
Fare Media
CharlieCard
CharlieTicket
Onboard Cash
CharlieCard
CharlieTicket
Onboard Cash
CharlieCard
CharlieTicket
CharlieCard
CharlieTicket
Adult/Senior/TAP/Student/Free
Single-Ride
Adult/Senior/TAP/Student
Transfer
Short (fares below the full value)
Single-Ride
Bus/Inner Express/Outer Express
Pass
LinkPass: Monthly/1-Day/7-Day
Pass
Commuter Rail Zone and
InterZone/Commuter Boat
Pass
CharlieTicket
Senior/TAP/Student
Pass
CharlieCard
CharlieTicket
AFC data are also provided at the modal level at which each transaction
occurs. Table A-2 lists the modal and summary categories used in the Post–
Fare Increase Impacts Analysis that was conducted for the 2007 MBTA fare
increase.
A.2
PRICE ELASTICITY ESTIMATION
Subsequent to the 2007 fare increase, CTPS conducted a Post–Fare Increase
Impacts Analysis, which was intended, in part, to test the accuracy of the
elasticities used for the Pre–Fare Increase Impacts Analysis that had been
conducted to project changes in ridership that would result from higher fares.
CTPS
3/28/2012
A-1
APPENDIX: SPREADSHEET MODEL METHODOLOGY
TABLE A-2
AFC Modal Categories
Mode
Bus/
Trackless
Trolley
Rapid
Transit
Local Bus
Inner Express Bus
Outer Express Bus
Red, Orange, Blue, Green, Silver Waterfront Subway
Silver Line Waterfront Surface
Silver Line Washington Street
Green Line Surface B, C, D, E
Mattapan High-Speed Line
AFC Equipment
Farebox
Farebox
Farebox
Faregate
Farebox
Farebox
Farebox/Validator
Farebox
The price elasticities used in the spreadsheet model for the present analysis of a
potential 2012 fare increase are based on the elasticities that the 2007 Post–
Fare Increase Impacts Analysis found to have been demonstrated in the actual
ridership impacts of the 2007 increase. In that analysis, CTPS used the
percentage change in trips and price for each fare payment category and
calculated the price elasticities. While the elasticities of smaller, individual
categories were likely unreliable, CTPS was able to determine realistic
elasticity figures for larger and more general categories. Those figures were
generally found to be more elastic than the elasticity inputs used in the 2007
Pre–Fare Increase Impacts Analysis, which had underestimated the ridership
loss from the 2007 fare increase.
It is admittedly difficult to isolate the effects of price elasticity on changes in
demand. Over the course of a year (in which time it is assumed that the effects
of price changes are largely internalized by the population), economic,
demographic, and other factors may play as much, if not more, of a role in
influencing transit demand than price. Indeed, the upcoming year promises to
be characterized by significant uncertainty with regard to these larger trends.
Table A-3 presents the elasticities used in the spreadsheet model categorized
by type of fare payment and mode. The types of fare payment are divided into
two categories: “single-ride” (or pay-per-ride) and “pass.” Elasticities are
further divided into several modal categories: bus, subway, surface light rail,
commuter rail, ferry, and THE RIDE. All modes have both single-ride and pass
price elasticities except for THE RIDE, which has only single-ride customers.
Based on the 2007 Post–Fare Increase Impacts Analysis, single-ride price
elasticities are assumed to be as or less elastic than pass price elasticities,
signifying that the spreadsheet model projects single-ride customers to be
slightly less responsive to changes in price than pass customers. The least
elastic of the single-ride modal price elasticities is that for THE RIDE,
followed by bus, parking, subway and surface light rail, ferry, and, finally,
commuter rail. Elasticities for seniors and students are also assumed to be less
elastic than those for adults. For pass price elasticities, commuter rail is the
least elastic of the modes. Express bus passes are the next-least elastic,
followed by the Senior and Student Pass, the Commuter Boat Pass, the
monthly Bus Pass and LinkPass, and the 1- and 7-Day LinkPasses.
A-2
3/28/2012
Boston Region MPO
APPENDIX: SPREADSHEET MODEL METHODOLOGY
TABLE A-3
Single-Ride and Pass Elasticities by Fare Type and Mode
Fare Type/Mode
Single-Ride
Bus
Adult
Senior
Student
Subway
Adult
Senior
Student
Surface Light Rail
Adult
Senior
Student
Commuter Rail
Adult
Half-Fare
Ferry
Adult
Half-Fare
THE RIDE
Parking
Pass
Bus
Inner Express
Outer Express
LinkPass
1-Day LinkPass
7-Day LinkPass
Commuter Rail
Ferry
Senior
Student
A.3
Elasticity
-0.20
-0.20
-0.15
-0.15
-0.25
-0.25
-0.15
-0.15
-0.25
-0.25
-0.20
-0.20
-0.35
-0.35
-0.25
-0.30
-0.30
-0.20
-0.12
-0.20
-0.30
-0.20
-0.20
-0.30
-0.35
-0.35
-0.10
-0.25
-0.15
-0.15
PRICE ELASTICITY
Price elasticity is the measure of either the expected or observed rate of change
in ridership relative to a change in fares if all other factors remain constant. On
a traditional demand curve that describes the relationship between price, on the
y-axis, and demand, on the x-axis, elasticities are equivalent to the slope along
that curve. Therefore, price elasticities are generally expected to be negative,
meaning that a positive price increase will lead to a decrease in demand (with a
price decrease having the opposite effect). The more negative (farther from
zero) the value of a price elasticity, the larger the projected decrease in
demand. More negative price elasticities are said to be relatively “elastic,”
while smaller negative values, closer to zero, are said to be relatively
“inelastic.” Thus, if the price elasticity of the demand for transit is assumed to
be elastic, a given fare increase would cause a greater loss of ridership than if
demand were assumed to be inelastic.
At its most elemental level, the spreadsheet model is based on this simple price
elasticity relationship, and requires four inputs: original demand, original fare,
new fare, and the price elasticity. The formula for calculating new demand is:
CTPS
3/28/2012
A-3
APPENDIX: SPREADSHEET MODEL METHODOLOGY
New Demand = Original Demand × [1 + Price Elasticity × (New Fare / Old Fare - 1)]
As an example, assume that original demand equals 100 and that the impact
that is being modeled is a 10 percent fare increase from $1.00 to $1.10. Also
assume that the price elasticity is -0.25.
New Demand = 100 × [1 + -0.25 × ($1.10 / $1.00 - 1)] = 97.50
Thus, using an elasticity of -0.25, a simple price elasticity model projects that a
10 percent increase in price will lead to a 2.50 percent decrease in demand.
With the fare increased from $1.00 to $1.10, this simplified model projects a
7.25 percent increase in revenue ($100.00 to $107.25).
A.4
DIVERSION FACTORS
The spreadsheet model’s calculations are more complex—and therefore more
accurate—than a simple elasticity calculation. Its greater complexity lies in its
use of ridership diversion factors. Diversion factors reflect estimates of the
likelihood of a switch in demand for one type of good to another as a result of a
change in the relative prices of those goods. In the spreadsheet model, such
factors are used for estimating the number of riders choosing to divert from one
fare/modal category to another.
Using cash tickets and passes as an example, assume that original ridership
equals 100 cash riders and 1,000 pass riders. Also assume that original prices
for cash tickets and passes equal $2.00 and $100.00, respectively, and that the
new prices are set at $1.50 for cash tickets and $50.00 for passes, representing
price decreases of 25 percent and 50 percent. Assume that the cash price
elasticity equals -0.35 and the pass price elasticity equals -0.25. Finally,
assume a cash-to-pass diversion factor of 0.05 and a pass-to-cash diversion
factor of 0.00.
In these calculations of diversion, one of the diversion factors must always
equal zero, indicating that the diversion is expected to occur in one direction
only. The direction of the diversion, and thus the diversion factor value,
depends on the respective price changes of the two types of goods. The
category with the greater relative price decrease (or the smaller relative price
increase)—in this case, pass, for which the price decrease is 50 percent,
compared to 25 percent for cash tickets—would gain riders from the diversion,
while the other category, with the smaller relative price decrease (or the greater
relative price increase), would lose riders from the diversion. One would
therefore expect that cash customers would switch to passes, but not that pass
customers would switch to cash tickets: hence the 0.05 cash-to-pass and 0.00
pass-to-cash diversion factors.
The diversion factors essentially work to redistribute demand between the two
categories after the respective price elasticities have been applied. For instance,
after the cash fare is decreased from $2.00 to $1.50, the projected effect of
price elasticity is that cash demand grows to 108.75 riders. Similarly, the pass
price decrease from $100 to $50 leads to a projected increase in pass demand,
due to price elasticity, to 1,125, for a total ridership of 1,233.75. However, the
A-4
3/28/2012
Boston Region MPO
APPENDIX: SPREADSHEET MODEL METHODOLOGY
percentage decrease in the pass price is larger than that in cash fares (50
percent versus 25 percent); thus, one would expect some customers to switch
from cash to pass.
This diversion is estimated by taking the ratio of new-to-original cash prices
($1.50/$2.00, or 75 percent), dividing that ratio by the ratio of new-to-original
pass prices ($50/$100, or 50 percent), subtracting 1, and multiplying this result
by the 0.05 diversion factor and the price-elasticity-estimated cash ridership
(108.75). The number of riders “diverted” from cash to pass equals 2.72,
giving final ridership estimates of 106.03 for cash and 1,127.72 for pass (still
summing, of course, to a total ridership of 1,233.75).
New Cash Demand (Price Effect), Cp = 100 [1 + -0.35 × ($1.50 / $2.00 - 1)] = 108.75
New Pass Demand (Price Effect), Pp = 1,000 [1 + -0.25 × ($50 / $100 - 1)] = 1,125.00
Total Demand = 108.75 + 1,125.00 = 1,233.75
Diverted Riders from Cash to Pass =  $ NewCash / $OldCash  − 1 × Diversion × C P
 $ NewPass / $OldPass




Diverted Riders from Cash to Pass =  $1.50 / $2.00  − 1 × 0.05 × C P = 2.72
 $50 / $100




New Cash Demand = Cp – Diverted Riders from Cash to Pass = 106.03
New Pass Demand = Pp + Diverted Riders from Cash to Pass = 1,127.72
Total Demand = 106.03 + 1,127.72 = 1,233.75
In the present impact analysis, diversion factors were used to estimate
diversions between cash and pass categories (for example, bus cash versus bus
pass, subway cash versus subway pass, etc.), between bus and rapid transit (in
other words, bus cash versus subway cash, bus pass versus subway pass, etc.),
and between CharlieTicket/onboard cash and CharlieCard (for example, bus
onboard cash versus bus CharlieCard, subway CharlieTicket versus subway
CharlieCard, etc.). The factors were determined based on the 2007 Post–Fare
Increase Impacts Analysis.
A.5
EXAMPLES OF RIDERSHIP AND REVENUE CALCULATIONS
A.5.1
SIMPLE EXAMPLE: PRICE ELASTICITY ONLY
•
•
•
•
Original Demand: 100,000
Original Fare: $1.50
New Fare: $2.50
Price Elasticity: -0.05
New Demand = 100,000 [1 + -0.05 × ($2.50 / $1.50 - 1)] = 96,666.67
CTPS
3/28/2012
A-5
APPENDIX: SPREADSHEET MODEL METHODOLOGY
A.5.2
MORE COMPLEX EXAMPLE: PRICE ELASTICITY PLUS RIDERSHIP
DIVERSION – CASH TO PASS
•
•
•
•
Original Cash Demand: 10,000
Original Cash Fare: $2.25
New Cash Fare: $2.00
Cash Price Elasticity: -0.30
New Cash Demand (Price Effect), Cp = 10,000 [1 + -0.30 × ($2.00 / $2.25 - 1)]
= 10,333.33
•
•
•
•
Original Pass Demand: 5,000
Original Pass Price: $71.00
New Pass Price: $50.00
Pass Price Elasticity: -0.25
New Pass Demand (Price Effect), Pp
= 5,000 [1 + -0.25 × ($50 / $71 - 1)]
= 5,369.72
Total Demand = 10,333.33 + 5,369.72 = 15,703.05
•
•
•
•
Percentage Change in Cash Price: $2.25 to $2.00: -11%
Percentage Change in Pass Price: $71 to $50: -30%
Cash to Pass Diversion Factor: 0.05
Pass to Cash Diversion Factor: 0.00
 $2.00 / $2.25  
P
 − 1 × 0.05 × C = 135.48
 $50 / $71  
Diverted Riders from Cash to Pass = 
New Cash Demand = Cp – Diverted Riders from Cash to Pass = 10,197.85
New Pass Demand = Pp + Diverted Riders from Cash to Pass = 5,505.20
Total Demand = 10,197.85 + 5,505.20 = 15,703.05
A.5.3
ADDITIONALLY COMPLEX EXAMPLE: PRICE ELASTICITY PLUS TWO
RIDERSHIP DIVERSIONS – SINGLE-RIDE CHARLIECARD (SR-CC) TO
PASS, AND SINGLE-RIDE CHARLIETICKET (SR-CT) TO SINGLE-RIDE
CHARLIECARD (SR-CC)
•
•
•
•
Original Single-Ride CharlieCard Demand: 10,000
Original Single-Ride CharlieCard Fare: $2.20
New Single-Ride CharlieCard Fare: $3.50
Single-Ride CharlieCard Price Elasticity: -0.30
New SR-CC Demand (Price Effect), CCp = 10,000 [1 + -0.30 × ($3.50 / $2.20 - 1)]
= 8,227.27
A-6
3/28/2012
Boston Region MPO
APPENDIX: SPREADSHEET MODEL METHODOLOGY
•
•
•
•
Original Pass Demand: 50,000
Original Pass Price: $71.00
New Pass Price: $90.00
Pass Price Elasticity: -0.25
New Pass Demand (Price Effect), Pp
•
•
•
•
= 50,000 [1 + -0.25 × ($90 / $71 - 1)]
= 46,654.93
Original Single-Ride CharlieTicket Demand: 5,000
Original Single-Ride CharlieTicket Fare: $2.50
New Single-Ride CharlieTicket Fare: $4.50
Single-Ride CharlieTicket Price Elasticity: -0.30
New SR-CT Demand (Price Effect), CTp
= 5,000 [1 + -0.30 × ($4.50 / $2.50 - 1)]
= 3,800.00
Total Demand = 8227.27 + 46,654.93 + 3,800.00 = 58,682.20
•
•
•
•
•
•
•
Percentage Change in Single-Ride CharlieCard Fare: $2.20 to $3.50: 59.09%
Percentage Change in Pass Price: $71 to $90: 26.76%
Percentage Change in Single-Ride CharlieTicket Fare: $2.50 to $4.50: 80.00%
Single-Ride CharlieCard to Pass Diversion Factor: 0.05
Pass to Single-Ride CharlieCard Diversion Factor: 0.00
Single-Ride CharlieCard to Single-Ride CharlieTicket Diversion Factor: 0.00
Single-Ride CharlieTicket to Single-Ride CharlieCard Diversion Factor: 0.25
 $3.50 / $2.20  
Diverted Riders from SR-CC to Pass = 
 − 1 × 0.05 × CCp = 104.92
 $90 / $71  
Diverted Riders from SR-CT to SR-CC =  $4.50 / $3.50  − 1 × 0.25 × CTp = 79.80
 $3.50 / $2.20  
New Single-Ride CharlieCard Demand = CCp – Diverted Riders from SR-CC to Pass
+ Diverted Riders from SR-CT to SR-CC = 8,202.15
New Pass Demand = Pp + Diverted Riders from SR-CC to Pass = 46,759.85
New Single-Ride CharlieTicket Demand = CTp – Diverted Riders from SR-CT to
SR-CC = 3,720.20
Total Demand = 8,202.15 + 46,759.85 + 3,720.20 = 58,682.20
Note that as each additional ridership diversion factor is introduced, and more
and more cells in the spreadsheet become linked, the complexity of the
spreadsheet model increases significantly. However, the basics of the
methodology explained above with regard to price elasticities and ridership
diversion factors remain the same.
CTPS
3/28/2012
A-7