1

Transit Fare Elasticity –A WMATA Experience

Shi (Shelley) Xie*WMATA

11th TRB National Transportation Planning Application ConferenceDaytona Beach, Florida

May 6-10, 2007

* The views expressed herein are solely of the presenter and do not necessarily reflect the policies or positions of WMATA Board or its management team

2

Outline

• Background • Fare Structure• Metrorail Ridership• Methodology• Forecast vs. Actual• Conclusions

3

Background

• September 11, 2001 tragedy impact:

– Slowdown in regional economy: • slowing growth in weekday commuter trips• flattening growth in weekday off-peak and weekend trips• stalling growth in non-passenger revenues

– Slowdown in national economy: • reducing growth in tourism related trips• lacking major events and related trips

• Sharply raised operating expenses for Fiscal Year 2004 and 2005

• First fare change in 7 consecutive years

Fare Increase For FY04/FY05 Was InevitableFare Increase For FY04/FY05 Was Inevitable

4

Background (cont’)

• Metrorail passenger revenue is about 70 percent of all passenger revenues

• Metrorail ridership data-warehouse became available

and reliable – Time-of-day data

• Weekday peak (AM and PM)

• Weekday off-peak (Mid-day and Evening)

– Distance-based O/D data– Ridership by fare media data

• However, Metrobus data lagged – During the transition of changing fare collection technology

Metrorail Only DiscussionMetrorail Only Discussion

5

Washington Metropolitan Area Transit Authority Metrorail System

Metrorail System:

106.3 Miles

86 Stations

FY2006 Ridership:

205 million

Average Weekday Ridership (FY06):

750,000

2/3 peak trips

FY2007 Operating Budget:

$620.8 million

6

Fare Structure• Metrorail fare structure is a distance and time based fare

system:– Regular fare (or Peak Fare) includes a base boarding charge, tier

mileage charge and maximum fare elements

– Discounted fare (or Off-Peak Fare) includes three flat fares for each fare segment

Between 7-10 Composite Miles

$1.85/Trip

First 7 Composite Miles$1.35/Trip

Over 10 Composite Miles$2.35/Trip

0 miles 7 miles 10 miles 30 miles

Fare Elasticity Should Reflect Distance-based StructureFare Elasticity Should Reflect Distance-based Structure

$1.35 +$0.220/Mile

(Mileage Rate)

Base Fare$1.35

Maximum fare benefit-noadditional mileage charge for tripsgreater than 16 composite miles

Taper benefit $0.025/Mile

3 miles 6 miles 16 miles

Maximum Fare $3.90

30 miles

$2.01 +$0.195/Mile (Mileage Rate)

7

Fare Structure (cont’)

• Limited discount products: – Passes:

• Day Pass• Weekly Short-Trip Pass• Weekly Pass• Convention pass

– Other discount fare products• Elderly and Disabled• DC Student fare and Student SmartPass

Discount Products Accounts For Only A Small % of Used Fare MediaDiscount Products Accounts For Only A Small % of Used Fare Media

8

Understanding Metrorail Ridership

• Metrorail ridership growth rate is fairly stable– Steady federal or federal government related employment

• Very stabled commuter market: about 40% federal workers– Constant tourist stream

• Smithsonian museums and national park service attractions

• Metrorail discretionary ridership follows a seasonal pattern in a 12 months circle– Summer vacation-local vacation-Spring breaks-summer vacation

• Metrorail plays important roll in all special events – National events:

• Million Man March• State Funerals

– Local events:• Sports games, concerts, etc.

Fare Elasticity Should Be Low Compared to Other MarketsFare Elasticity Should Be Low Compared to Other Markets

9

Understanding Metrorail Ridership

• Distance-based trip distributions were fairly consistent– Roughly 50% of weekday peak trips were in base fare and 1st

tier fare segment (zero – 6 miles); the rest of weekday peak trips were split almost evenly between 6-10 mile segment and beyond 10 mile segment

– Weekday off-peak periods and weekend trips had over 60% in 1st fare segment, about 16% in 2nd fare segment and about 20% in 3rd fare segment

Trip Distribution before fare changes (2002 data)

Trip Length

Zero – 6/7 Miles 6/7 – 10 Miles > 10 Miles

Weekday Peak 48.3% 26.5% 25.2%

Weekday Off-Peak 64.8% 16.9% 18.3%

Saturday 60.0% 16.5% 23.5%

Sunday 62.6% 16.1% 21.3%

Fare Elasticity Matrix Would Break Upon Those Trip LengthsFare Elasticity Matrix Would Break Upon Those Trip Lengths

10

Methodology - Things to consider

• Lack of research or study on transit fare elasticity, especially on distance-based fare elasticity

• WMATA’s last fare elasticity study was done in early 1990s– The study was intended to do distance-based fare elasticity– Lack of data was the main hurdle in accomplishing the task

• WMATA’s unique market – Large percentage of federal government commuters– Very seasonal ridership pattern, influenced by tourism

• Unique transit incentives: – MetroChek / SmartBenefit

• Most federal and some private employees receive $110 per month

• Budgetary request– Measure revenue impact for every fare element

Create Customized Fare Elasticity MatrixCreate Customized Fare Elasticity Matrix

11

Methodology - Assumptions

• Assumptions– Fare elasticity for Metrorail would be lower than transit industry

standards• Strong and stable commuter market• High transit incentive

– Weekday trips would be less elastic than that for weekend trips• Small portion of discretionary trips on weekdays • High percentage of discretionary trips on weekends

– Suburban long-distance commuter trips would be less elastic than short-distance trips

• Less alternatives for long-distance trips: long and unpredictable commuting time as the results of traffic congestion, lack of downtown parking, etc.

• More alternatives for short-distance trips: taxi, bike, walk, etc.

Bases for Elasticity MatrixBases for Elasticity Matrix

12

Methodology - Elasticity Matrix

• Elasticity (k-factor) matrix includes the following variables: time-of-day pricing, trip length and percent fare change– For weekday regular (peak) fare:

% Change in Fare

Trip Length

Zero – 6 Miles 6 – 10 Miles > 10 Miles

< 10% -0.15 -0.125 -0.075

10-15% -0.20 -0.175 -0.100

>15% but <25% -0.25 -0.225 -0.100

% Change in Fare

Trip Length

Zero – 7 Miles 7 – 10 Miles > 10 Miles

< 10% -0.20 -0.175 -0.100

10-15% -0.30 -0.275 -0.100

>15% but <25% -0.30 -0.275 -0.200

– For weekday off-peak discount fare:

13

Methodology - Elasticity Matrix (cont’)

• Elasticity (k) matrix includes the following variables: time-of-day pricing, trips length and percent fare change– For weekend discount fare:

% Change in Fare

Trip Length

Zero – 7 Miles 7 – 10 Miles > 10 Miles

< 10% -0.25 -0.20 -0.15

10-15% -0.35 -0.30 -0.25

>15% but <25% -0.35 -0.30 -0.25

14

Methodology - Fare Model

• Fare model to reflect WMATA’s fare structure– Can measure revenue impact for each fare segment

Metrorail Model

Fare Changes Peak % change Off Peak % change

Base $0.00 0% $0.00 0% Annual Impact (in 1,000s)

Maximum $0.00 0% Revenue $0 0.00%

1st tier $0.00 0% $0.00 0% Ridership - 0.00%

2nd tier $0.00 0% $0.00 0%Fast Pass $0.00 0%Day Pass $0.00 0%

Min. Mid Max Current Average Fare $1.99

Elasticity Factor Peak 0.150 0.125 0.075 New Average Fare $1.99

Off-Peak 0.200 0.175 0.100

Weekend 0.250 0.200 0.150

Annualization Factor Weekday 255Weekend 55

Difference - $0 - $0 - $0 - $0

Off-Peak PassWeekendPeak

15

Methodology - Fare Model (cont’)

• Then, inputting fare change proposals into model – One or multiple fare elements

Current Fare StructureSaturday Sunday

Peak Off Peak AM Peak PM Peak AM Peak PM Peak Midday Evening Midday Evening Saturday Sunday

Intra Station $1.35 $1.35 1,083 1,333 $1,463 $1,800 1,105 693 $1,492 $936 3,190 2,138 $4,306 $2,8870 - 3 Mile $1.35 $1.35 43,896 56,029 $59,259 $75,640 44,635 17,417 $60,257 $23,512 76,973 51,645 $103,914 $69,7203 - 4 Mile $1.45 $1.35 24,876 26,854 $36,070 $38,939 16,334 9,489 $22,051 $12,811 36,247 24,343 $48,934 $32,8634 - 5 Mile $1.70 $1.35 19,636 20,929 $33,381 $35,580 12,753 7,402 $17,217 $9,993 28,296 19,835 $38,199 $26,7775 - 6 Mile $1.90 $1.35 14,072 14,290 $26,737 $27,152 7,742 4,799 $10,452 $6,478 20,647 13,853 $27,873 $18,7016 - 7 Mile $2.10 $1.35 15,607 14,827 $32,776 $31,137 6,821 4,318 $9,208 $5,829 14,538 10,043 $19,626 $13,5577 - 8 Mile $2.30 $1.85 17,589 17,173 $40,456 $39,497 8,232 5,472 $15,230 $10,123 21,891 14,132 $40,499 $26,1448 - 9 Mile $2.50 $1.85 17,495 16,037 $43,737 $40,093 6,474 3,943 $11,976 $7,295 15,896 10,661 $29,407 $19,7249 - 10 Mile $2.70 $1.85 15,570 14,022 $42,040 $37,858 5,400 3,663 $9,989 $6,777 13,570 8,902 $25,104 $16,46910 - 11 Mile $2.90 $2.35 15,517 14,405 $44,998 $41,774 5,752 3,697 $13,516 $8,688 15,621 10,459 $36,709 $24,57811 - 12 Mile $3.10 $2.35 11,129 10,043 $34,501 $31,134 4,017 2,572 $9,439 $6,044 10,253 7,004 $24,094 $16,45812 - 13 Mile $3.30 $2.35 9,334 8,474 $30,803 $27,965 3,155 2,284 $7,415 $5,366 8,826 6,236 $20,741 $14,65413 - 14 Mile $3.50 $2.35 8,125 7,236 $28,439 $25,325 2,651 1,764 $6,231 $4,146 7,829 4,614 $18,399 $10,84414 - 15 Mile $3.70 $2.35 7,758 7,142 $28,706 $26,425 2,769 1,820 $6,506 $4,277 10,047 6,186 $23,611 $14,53815 - 16 Mile $3.85 $2.35 3,489 3,092 $13,432 $11,905 1,370 817 $3,220 $1,919 4,502 3,643 $10,580 $8,56116 - 17 Mile $3.90 $2.35 3,872 3,297 $15,101 $12,859 1,184 958 $2,782 $2,252 2,698 2,171 $6,340 $5,10317 - 18 Mile $3.90 $2.35 3,304 3,020 $12,887 $11,777 1,005 754 $2,361 $1,772 4,369 3,393 $10,267 $7,97318 - 19 Mile $3.90 $2.35 2,354 2,088 $9,179 $8,144 821 455 $1,930 $1,069 3,752 2,056 $8,817 $4,83119 - 20 Mile $3.90 $2.35 1,137 958 $4,435 $3,737 333 257 $783 $604 1,060 892 $2,491 $2,097> 20 Mile $3.90 $2.35 1,908 1,656 $7,442 $6,460 654 476 $1,537 $1,119 3,041 4,420 $7,147 $10,386

237,753 242,908 $545,841 $535,202 133,206 73,050 $213,591 $121,011 303,245 206,625 $507,057 $346,865$2.30 $2.20 $1.60 $1.66

Peak 480,661 $1,081,043 $2.25 Off-Peak 206,256 $334,602 $1.62 Weekend 509,870 $853,922 $1.67Annual 122,568,555 $275,665,923 52,595,280 $85,323,541 28,042,850 $46,965,732

Pass use ridership Weekday pass 35,500 Weekend 43,300 214,640,685 Annual 9,052,500 2,381,500 Annual Total Pass 11,434,000 $427,955,197

Pass Revenue 20,000,000$ $1.99

Weekend RevenueFare Weekday Off-Peak RevenueWeekday Peak Weekday Peak Revenue Weekday Off Peak

• First, validating fare model with no-fare impact projection – Matching total targeted ridership and revenue figures

16

Methodology - Fare Model (cont’)

• Sample of the application: Fare Changes Peak % change Off Peak % change

Base $0.10 7% $0.10 7% Annual Impact (in 1,000s)

Maximum $0.25 6% Revenue $22,344 5.22%

1st tier $0.01 5% $0.10 5% Ridership (2,069) -0.96%2nd tier $0.01 5% $0.10 4%Fast Pass $0.00 0%Day Pass $0.00 0%

Min. Mid Max Current Average Fare $1.99

Elasticity Factor Peak 0.150 0.125 0.075 New Average Fare $2.12

Off-Peak 0.200 0.175 0.100

Weekend 0.250 0.200 0.150

Annualization Factor Weekday 255Weekend 55

Difference (1,040,395) $15,923,139 (627,338) $4,266,933 (401,112) $2,154,181 - $0

NEW Fare StructureSaturday Sunday

Peak Off Peak AM Peak PM Peak AM Peak PM Peak Midday Evening Midday Evening Saturday Sunday

Intra Station $1.45 $1.45 1,071 1,319 $1,553 $1,912 1,088 683 $1,578 $990 3,131 2,099 $4,540 $3,0430 - 3 Mile $1.45 $1.45 43,408 55,407 $62,942 $80,340 43,973 17,159 $63,761 $24,880 75,548 50,688 $109,544 $73,4983 - 4 Mile $1.56 $1.45 24,593 26,549 $38,365 $41,416 16,092 9,349 $23,333 $13,556 35,576 23,892 $51,585 $34,6444 - 5 Mile $1.82 $1.45 19,428 20,708 $35,359 $37,688 12,564 7,292 $18,218 $10,574 27,772 19,468 $40,269 $28,2285 - 6 Mile $2.03 $1.45 13,928 14,144 $28,273 $28,712 7,627 4,728 $11,060 $6,855 20,264 13,596 $29,383 $19,7146 - 7 Mile $2.24 $1.45 15,477 14,704 $34,669 $32,936 6,720 4,254 $9,744 $6,168 14,269 9,857 $20,689 $14,2927 - 8 Mile $2.45 $1.95 17,446 17,033 $42,743 $41,730 8,155 5,420 $15,901 $10,569 21,655 13,979 $42,227 $27,2608 - 9 Mile $2.66 $1.95 17,355 15,909 $46,164 $42,318 6,412 3,906 $12,504 $7,617 15,724 10,546 $30,661 $20,5659 - 10 Mile $2.87 $1.95 15,448 13,911 $44,335 $39,925 5,348 3,629 $10,429 $7,076 13,423 8,806 $26,175 $17,17210 - 11 Mile $3.08 $2.45 15,444 14,338 $47,569 $44,160 5,727 3,681 $14,031 $9,020 15,521 10,392 $38,026 $25,46011 - 12 Mile $3.29 $2.45 11,078 9,997 $36,447 $32,891 4,000 2,561 $9,799 $6,274 10,188 6,959 $24,959 $17,04912 - 13 Mile $3.50 $2.45 9,292 8,436 $32,521 $29,525 3,142 2,274 $7,698 $5,571 8,770 6,196 $21,486 $15,18013 - 14 Mile $3.71 $2.45 8,089 7,203 $30,009 $26,724 2,640 1,757 $6,468 $4,304 7,779 4,585 $19,059 $11,23314 - 15 Mile $3.92 $2.45 7,724 7,110 $30,277 $27,871 2,757 1,812 $6,754 $4,440 9,983 6,147 $24,459 $15,05915 - 16 Mile $4.08 $2.45 3,473 3,078 $14,171 $12,559 1,364 813 $3,343 $1,992 4,473 3,620 $10,959 $8,86816 - 17 Mile $4.14 $2.45 3,853 3,282 $15,953 $13,588 1,179 954 $2,888 $2,338 2,681 2,158 $6,567 $5,28617 - 18 Mile $4.15 $2.45 3,289 3,005 $13,647 $12,471 1,000 751 $2,451 $1,840 4,341 3,371 $10,636 $8,26018 - 19 Mile $4.15 $2.45 2,342 2,078 $9,721 $8,624 818 453 $2,004 $1,109 3,728 2,043 $9,133 $5,00419 - 20 Mile $4.15 $2.45 1,132 954 $4,696 $3,957 332 256 $813 $627 1,053 886 $2,581 $2,172> 20 Mile $4.15 $2.45 1,899 1,648 $7,881 $6,841 651 474 $1,595 $1,162 3,022 4,392 $7,404 $10,759

235,769 240,812 $577,296 $566,190 131,590 72,206 $224,373 $126,962 298,899 203,678 $530,343 $362,746$2.45 $2.35 $1.71 $1.76

Peak 476,581 $1,143,487 $2.40 Off-Peak 203,796 $351,335 $1.72 Weekend 502,577 $893,089 $1.78Annual 121,528,160 $291,589,062 51,967,942 $89,590,474 27,641,738 $49,119,914

Pass use ridership Weekday pass 35,500 Weekend 43,300 212,571,840 Annual 9,052,500 2,381,500 11,434,000 $450,299,450

Pass Revenue 20,000,000$ $2.12

Weekday Off Peak Weekday Off-Peak Revenue Weekend RevenueWeekday Peak Weekday Peak Revenue

Off-Peak PassWeekendPeak

17

Fare Package for FY04 and FY05

• Regular (peak) fare:

Zero – 3 Miles

(Base Fare)

3 – 6 Miles

(Mileage Rate)

6 – 15 Miles

(Mileage Rate)

Max Fare

Original $1.10 $0.19 $0.165 $3.25

FY2004 $1.20 $0.21 $0.185 $3.60

FY2005 $1.35 $0.22 $0.195 $3.90

• Discount (off-peak) fare:

Zero – 7 Miles 7 – 10 Miles 10 Miles & over

Original $1.10 $1.60 $2.10

FY2004 $1.20 $1.70 $2.20

FY2005 $1.35 $1.85 $2.35

18

Fare Package for FY04 and FY05 (Cont’)

• FY2004 fare increase penalized long distance trips– Less than 10% increase on base fare and discount fare, but– More than 10% increase on 1st and 2nd tier mileage charge and

max-fare

• FY2005 fare increase had a reverse impact– More than 10% base fare increase– Less than 10% increase on 1st and 2nd tier mileage charge and

max-fare

• For both years, the fare matrix was essential to dealing with variety of fare changes, and helped to create accurate projections

19

Forecast vs. Actual

• Actual ridership for the two fiscal years that had fare increases were very close to projections

180

190

200

210

FY02 FY03 FY04 FY05 FY06

Rid

ers

hip

(in

Mill

ions)

Budget Actual

Sept. 11

Surge gas price Return of National Baseball team

Fare increase

20

Ridership - After Fare Changes

• Distance-based trip distributions were mostly consistent with the pattern before fare change with expected fare elasticity impact – Share of trips with the highest elasticity (0-6 mile) dropped most – Share of trips between 6 and 10 miles changed slightly– Share of trips traveled beyond 10 miles increased

• Partly due to new Largo extension opening

• Weekday off-peak and Saturday ridership were mostly consistent with the pattern before fare change

• Sunday ridership distribution changed the most, reflecting the discretionary and unpredictable trip nature of these types of trips

Elasticity Matrix Seems ValidElasticity Matrix Seems Valid

21

Ridership – The Differences

• Post fare change distribution:

Trip Distribution Difference

Trip Length

Zero – 6/7 Miles 6/7 – 10 Miles > 10 Miles

Weekday Peak -1.9% 0.2% 1.7%

Weekday Off-Peak -0.1% -0.8% 0.9%

Saturday -0.7% 0.4% 0.2%

Sunday -3.6% 0.2% 3.4%

Trip Distribution after fare changes

Trip Length

Zero – 6/7 Miles 6/7 – 10 Miles > 10 Miles

Weekday Peak 46.4% 26.7% 26.9%

Weekday Off-Peak 64.7% 16.1% 19.2%

Saturday 59.3% 16.9% 23.7%

Sunday 59.0% 16.3% 24.7%• The difference (compared to the table on Slide 9) :

22

Conclusions and Suggestions

• It is an empirical study.• Further improvement of the fare model is needed:

– Maxfare: how to deal with maxfare which is discounted fare– Cross-elasticity: how to combine parking fee increase with fare

increase

• Further econometric analysis is needed– Especially for distance-based fare structure

23

Acknowledgement

• Thanks to my colleagues in Office of Management and Budget Services for their suggestions and support

• Thanks to my current director for giving me the green light to finish my “old” job.