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Crossing the Bridge: The Effectiveness of Time-Varying Tolls on Curbing Bay Area Congestion Kate Foreman UC Berkeley Camp Resources August 7, 2012.

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Presentation on theme: "Crossing the Bridge: The Effectiveness of Time-Varying Tolls on Curbing Bay Area Congestion Kate Foreman UC Berkeley Camp Resources August 7, 2012."— Presentation transcript:

1 Crossing the Bridge: The Effectiveness of Time-Varying Tolls on Curbing Bay Area Congestion Kate Foreman UC Berkeley Camp Resources August 7, 2012

2 Current road pricing is suboptimal “In no other major area are pricing practices so irrational, so out of date, and so conducive to waste as in urban transportation. … particularly deficient: the absence of adequate peak-off differentials…” William Vickrey, AER, 1963 2Kate Foreman (Berkeley) - Crossing the Bridge

3 Congestion is costly EPA estimates that transportation: – contributes 27% of US GHG emissions – is the fastest-growing source of US GHG emissions Annual urban road congestion costs in US include: – $115b 3.9b gallons of wasted fuel (34m mtCO 2 ) 4.8b hours of travel delay – $31b mortality cost due to particulate matter 3 Kate Foreman (Berkeley) - Crossing the Bridge

4 Theory favors price mechanisms to address congestion Solution to road congestion externalities: – Baumol & Oates (1988) Pigouvian tax equal to marginal social damage – Boardman & Lave (1977) Pricing must vary by time of day – Anas & Rhee (2006) Pricing is first-best Non-pricing is not second-best (boundary roads harmful) 4Kate Foreman (Berkeley) - Crossing the Bridge

5 Congestion pricing seldom implemented & literature lacks empirical analysis Examples: – Cordon pricing (London, Milan, Stockholm…) – Off-peak discount (Lee County) – Static & dynamic variable time pricing (Orange County, Singapore, San Diego) Literature – Davis (2008): driving restrictions in Mexico ineffective – Brownstone et al (2003): WTP for travel time=$30/hr – Industry reports (Milan, Bay Area) Kate Foreman (Berkeley) - Crossing the Bridge5

6 6 Bay Bridge: 124,000 (62%) San Mateo Bridge: 46,000 (23%) Dumbarton Bridge: 31,000 (15%) Westward traffic volume per day on three bridges

7 Toll changes on July 1, 2010 were not the same on all bridges Congestion pricing introduced on Bay Bridge BridgeBeforeAfter PeakOff peak RegularCarpoolRegularCarpoolRegularCarpool Bay$4Free$6$2.50$4N/A San Mateo & Dumbarton $4Free$5$2.50$5N/A 7Kate Foreman (Berkeley) - Crossing the Bridge

8 Predictions from theory due to toll changes: – Decrease in traffic volume and travel time during peaks due to: – Trip reduction (combining, avoidance) – Time-shifting (from peak to off-peak hours) – Route-shifting (to San Mateo Bridge) – Mode-shifting – From ride-sharing (carpool) to solo driving (Fastrak/cash) – From driving to public transit (BART, bus) 8 Theory predicts decreases in traffic volume and travel time on the Bay Bridge Kate Foreman (Berkeley) - Crossing the Bridge

9 My research question tests the theory Did the introduction of time-of-day congestion pricing on the Bay Bridge decrease traffic volume and travel time during peak hours? 9Kate Foreman (Berkeley) - Crossing the Bridge

10 My data span the year before and year after the toll changes for 3 bridges Hourly volume (# vehicles crossing), by lane – Lane type: Fastrak, cash, carpool Hourly travel time (median # minutes to cross) 1 year before & after change: – 1 July 2009 - 30 June 2011 Weekdays, westbound, excluding holidays 10Kate Foreman (Berkeley) - Crossing the Bridge

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13 Diffs in diffs approach to estimate of average treatment effect 13Kate Foreman (Berkeley) - Crossing the Bridge Y hdw = α 0 + α h + β 0 after w + β h after w + γ d + θ w + ε hdw Y hdw = outcome variable (traffic volume or travel time) h is hour of day d is day of week w is week of sample after = indicator for after policy change on July 1, 2010 α h = hour of the day FE (1-23) γ d = day of the week FE (TWRF) θ w = week of sample FE (1-7 Jan excluded) β h = coefficient of interested (policy ATE for each hour)

14 14Kate Foreman (Berkeley) - Crossing the Bridge Time-varying congestion pricing worked to decrease traffic overall & shift travel from peak to off-peak!

15 15Kate Foreman (Berkeley) - Crossing the Bridge Time-varying congestion pricing worked to shift morning peak travel from Bay to San Mateo?

16 16Kate Foreman (Berkeley) - Crossing the Bridge Time-varying congestion pricing didn’t affect Dumbarton (but price increase  volume decrease).

17 17Kate Foreman (Berkeley) - Crossing the Bridge Time-varying congestion pricing worked to decrease travel time during peak hours on Bay Bridge!

18 18Kate Foreman (Berkeley) - Crossing the Bridge San Mateo Bridge absorbed any extra traffic without increasing travel time.

19 No effect on travel time on the Dumbarton. 19Kate Foreman (Berkeley) - Crossing the Bridge

20 Positive welfare impacts of time-varying congestion pricing on Bay Bridge Time savings – Bounded: $6.6m - $27.6m (@$30/hr) Fuel savings – 280,000 gallons/year  $1.1m/year Emissions abatement – 2,700tCO 2 /year  $54,000/year (@$20/tCO 2 ) 20Kate Foreman (Berkeley) - Crossing the Bridge

21 Conclusions Congestion pricing works to decrease traffic volume and travel time – Trip reduction – Time shifting: vehicles switch from peak to off-peak – Route shifting: substitution toward non-congestion priced bridge Bridge absorbed extra traffic without increasing travel time – Mode-shifting: substitution from carpool to non- carpool lanes 21Kate Foreman (Berkeley) - Crossing the Bridge

22 Next Steps Integrate public transit data (BART and bus) to estimate substitution & cross price elasticities Calculate additional welfare implications Include estimates of changes in travel time variance 22Kate Foreman (Berkeley) - Crossing the Bridge


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