Evans School Review Vol. 2, Num. 1, Spring 2012 A Benefit ... · Evans School Review Vol. 2, Num....

Evans School Review Vol. 2, Num. 1, Spring 2012

26

A Benefit-Cost Analysis of

Road Pricing in Downtown

Seattle By Steven Danna, Keibun Mori, Jake Vela & Michelle Ward

ABSTRACT

This benefit-cost analysis evaluates the key benefits and costs

associated with potential cordon-based road pricing in downtown

Seattle to determine if this road pricing option will be beneficial

for the region. The accrued benefits quantified in this analysis are

(1) reduced travel time, (2) increased travel reliability, (3) reduced

emissions, and (4) reduced traffic accidents. On the cost side, the

study measures (1) capital and operation costs of the toll collection

system, (2) additional subsidy for transit agencies to meet higher

demand, and (3) both direct and indirect financing costs. The toll

revenues from road pricing and changes in other government

revenues such as gas tax are neutral for the society as a whole,

because they represent cash transfer between government and

residents and do not cause adverse impacts on social welfare unless

the toll rates are dramatically high. The results over a thirty-year

period show that there will be net benefits of 585 million dollars in

present value for the region in the base scenario. The extensive

sensitivity and uncertainty analysis also demonstrate that the

project will remain favorable in conservative scenarios. The study

qualitatively examines possible impacts on other factors such as

retail sales and land use but concludes that they are unlikely to

undermine the key results in this analysis. These findings suggest

that in sum, road pricing in downtown Seattle would have positive

impacts for the city and region.

Keibun Mori completed his MPA at the Evans School focusing on energy and environmental policy. He is specialized in forecasting long-term energy demand and analyzing policy solutions to curb greenhouse gas emissions, with experience in assisting energy policy overhaul at the Washington State Department of Commerce and for the Ministry of the Environment of Japan. He can be contacted at [email protected].


A Benefit-Cost Analysis of Road Pricing in Downtown Seattle 27

I. INTRODUCTION

Seattle has the ninth most congested roadways in America; in 2010, an average driver in the

Seattle metro area spent 44 hours in traffic delays (Texas Transportation Institute 2011). Traffic

congestion causes fuel waste, which amounted to 46 million gallons of gasoline in the region in

2010, and this leads to decline in air quality and additional greenhouse gas (GHG) emissions

(Texas Transportation Institute 2011). Economists argue that traffic congestion is the

consequence of a market failure, as the private costs of driving (mostly fuel costs) do not account

for its social costs, such as the adverse impacts on roadway capacity and air quality (Downs

2007).

Road pricing can simultaneously solve these problems by internalizing these social costs

into the private costs of driving; the added costs induce some drivers to take a trip by other

means such as public transportation (Johansson and Mattsson 1994). Road pricing can be in a

variety of forms such as a gas tax, toll on freeways and bridges, and vehicle miles traveled

(VMT) tax, but road pricing on vehicles crossing a designated cordon has gained traction among

policy makers in recent decades (Johansson and Mattsson 1994). This cordon-based road pricing

is effective in deterring single-occupancy vehicles (SOV) to enter the city center, and Singapore

established the world’s first cordon-based road pricing scheme in 1975 to alleviate its persistent

traffic jam in its city center (SMOT 2012). The invention of electronic tolling systems in the late

20th

century reduced the costs of toll collection and prompted several European cities such as

London, Stockholm, and Milan to follow Singapore’s success in the 2000s (Rotaris et al. 2010).

Evans (2007) conducted benefit-cost analysis on the road pricing in London, finding that the

benefits from road pricing, primarily shorter travel time and increased travel reliability, exceed

its costs by a ratio of 1.5. Similarly, Eliasson’s (2008) benefit-cost analysis shows that a trial

program in Stockholm yielded significant net benefits from reduced congestion, and it would

take only four years to recoup the initial capital investment.

The demonstrated success of the London and Stockholm road pricing projects indicates

that road pricing may be a feasible policy option for Seattle to alleviate the traffic delay and its

adverse impacts. To estimate the costs and benefits for Seattle, this study assumes that the City

of Seattle will follow the example of these cities by:



Constructing and maintaining open-road electronic tolling facilities, similar to the

tolling system on the SR-520 Bridge connecting Seattle and Bellevue

Charging $2.15 per entry on weekdays only, an initial rate used in Stockholm

(Eliasson 2008), to the vehicles entering the designated cordon, defined by the

Puget Sound to the west, by the I-5 to the east, by Denny Way to the north, and S

King St. to the south (see areas defined by the blue lines in Figure 1)

Providing subsidies to King County Metro, a local transit agency, to increase the

level of transit service to accommodate increased demand for transit

Exempting special service vehicles such as transit and emergency vehicles

The following section outlines the methodology used to predict behavioral change and its

impacts. The subsequent sections estimate and aggregate various costs and benefits, then provide

qualitative discussions of other possible effects. After uncertainty and sensitivity analyses, this

study concludes with policy implications for Seattle.



Figure 1. Designated Cordon and Weekday Traffic Volume Source(s): SDOT 2003.



II. METHODOLOGY

The central assumption of this analysis is that vehicle trips into downtown Seattle have social

costs that drivers do not consider, in addition to its private costs such as the costs of fuel,

insurance, and maintenance. The social costs consist of the decreased reliability and increased

travel time, traffic accidents, and emissions from fuel consumption. Since drivers tend to neglect

these social costs when choosing to drive into the city center, the total number of vehicle trips is

larger than is otherwise socially optimal. Figure depicts a simplified market for vehicle trips

before (left) and after (right) road pricing. The demand curve represents the marginal value of

each vehicle trip to drivers.

Currently drivers take vehicle trips until their marginal costs of driving into downtown

equalize to the marginal benefits, but at this equilibrium point, the number of trips exceeds the

socially optimal point. This leads to a loss of social welfare, called deadweight loss, as shaded in

blue in Figure 2. By charging vehicles entering downtown, road pricing increases the private

costs of vehicle trips to match its social costs. This decreases the number of vehicle trips and

subsequently lowers or eliminates the welfare loss.

Figure 2. Market for Vehicle Trips before (Left) and after Road Pricing (Right)

To forecast this change in the number of vehicle trips to the city center, this study uses

the price elasticity of demand for vehicle trips. The elasticity represents the percentage change in



vehicle trips for every percentage change in the price of a trip. For example, an elasticity of -0.5

implies that increasing the cost of driving by 10% will lower vehicle trips of 5%. Using the price

elasticity of demand, the following equation can determine the change in the number of vehicle

trips:

where represents the price elasticity of vehicle trips into the city center.

Table 1 summarizes the parameters used to estimate the impacts on traffic volume. The

price elasticity of the number of vehicle trips in the table is from the survey on the observed

traffic change with similar road pricing schemes in London, Stockholm, and Milan (Transport

for London 2008; Evans 2008; Rotaris et al. 2010). Seattle’s drivers may be more or less

responsive to road pricing, so the Monte Carlo simulation addresses this uncertainty in the price

elasticity in the sensitivity analysis. When assuming the average toll rate to be in the range of $2

and $3 per entry, this model suggests that road pricing would curb the traffic volume by 12% to

30% as shown in Figure 3.

Table 1. Summary of Parameters for Traffic Volume Estimation

Parameter Value Note

Elasticity -0.4 ~ -0.6* Derived from observed data in

London, Stockholm, and Milan

Driving cost (fuel, insurance, vehicle

costs)

$0.5 per mile AAA’s survey (US average)

Average commute distance to the city

center

12.8 miles PSRC’s survey

Number of annual weekday vehicle

trips to the city center

125 million

trips

City of Seattle’s survey

Source(s): American Automobile Association (AAA) 2008; Evans 2008; Puget Sound Regional Council (PSRC)

2007; Seattle Department of Transportation 2003.



Figure 3. Number of Annual Averted Vehicle Trips

These forecasted changes in the number of vehicle trips are the basis for the rest of this

analysis. In order to estimate its impacts on other parameters, this study assumes constant

relationships between the changes in vehicle volume and those for other parameters. Table 2

shows these constant relationships in elasticities, which express the degree of response to

changes in vehicle volume for each parameter. These elasticity estimates come from the

observed data in London, Stockholm, and Milan (Roritas et al. 2010), and they can predict the

percentage changes of various parameters for the Seattle metro area with respect to changes in

vehicle trips.

Table 2. Elasticities of Various Parameters to Changes in Vehicle Trips

Parameter Elasticity % Change ($2.15 toll per entry)

Greenhouse gas (GHG) emissions 0.5042 -12.0%

Carbon monoxide (CO) emissions 0.5882 -14.0%

Nitric oxide (NO) emissions 0.3571 -8.5%

Particulate matters (PM) emissions 0.5882 -14.0%

Traffic accidents 0.1513 -3.6%

Total travel time

(travel time outside the cordon included) 0.1471 -3.5%

Transit ridership -0.6480 +9.2%

0

5

10

15

20

25

30

35

40

Toll=$2.00 Toll=$2.50 Toll=$3.00

Mill

ion

s Tr

ips

Elasticity=-0.4

Elasticity=-0.5

Elasticity=-0.6



III. DIRECT COSTS AND BENEFITS

Capital and Operation Costs

It is challenging to estimate the capital and operation costs for road pricing in Seattle since the

costs vary from location to location and data from comparable projects are scarce. Stockholm

can provide useful figures for Seattle with some adjustments to account for differences in

roadway configuration and average income, because Seattle’s size and geographical features

roughly correspond to those for Stockholm (Popenoe 2001). Adopting the cost estimates for

Stockholm by Eliasson (2008), the capital costs would be $362 million,1 including the costs of

planning, public outreach, and construction of the toll system. The operation would cost $38.9

million per year, including the costs of toll collection, enforcement, and the toll system

replacement.2

For the financing costs for the capital expenditures, this analysis considers three

alternative financing methods:

Twenty-year bond structured with level debt-service payments

Twenty-year bond structured with level principal payments

One-time tax levy (no financing)

For the two bonding options, the assumed annual effective coupon rate is 5%, based on

fixed-coupon bonds issued in Washington State in the past several years. Using this baseline

coupon rate, the capital costs including financing costs would be $674 million for the level-debt

service option.

It is also possible to levy property or sales tax to fund capital costs of infrastructure

projects in Seattle. In this case, there are no direct financing costs for Seattle, but taxes do have

indirect costs called “shadow price” (Campen 1986). This shadow price, or marginal excess tax

burden (METB), represents welfare loss caused by taxes that create economic inefficiency.

Judging from the findings by Ballard et al. (1985a) and Jorgensen et al. (1990), the analysis sets

METB at 17% of the tax levy. When accounting for this shadow price of tax levy, the capital

1 A simple conversion from Swedish Krona to US dollar is $272 million, but it was inflated by a third because the

cordon for Seattle proposed in this paper requires the number of toll points to be approximately 33% higher than

Stockholm’s. 2 A simple conversion from Swedish Krona to US dollar is $32 million, but it was inflated to $38.9 million per year

to account for wage difference for administrative jobs between the two cities, based on the assumption that the half

of the operation costs are labor costs.



costs will amount to $424 million. The toll revenues themselves do not incur METB because toll

is an excise tax on goods with negative externalities (Zerbe and Dively 1994).

Transit Subsidy

The large number of averted vehicle trips is likely to increase the demand for mass transit.

Transport for London (2008) found an increase in transit ridership entering and exiting the

downtown cordon in London, with an increase in the speed of city buses and a decrease in wait

time for passengers due to greater reliability in the bus schedule. Similarly, in Stockholm, transit

ridership rose by 6% with road pricing, with most of the increase directly attributed to road

pricing (Eliasson 2008). The quality of transit system and land use patterns influence the degree

to which road pricing impacts transit ridership, but this study assumes that the commuters in

Seattle will show similar responses to road pricing, and that the impact on destination choice

would be negligible. Table 3 summarizes the parameters used to estimate the additional subsidy

for transit to provide an affordable alternative and avoid overcrowding of the transit system.

Table 3. Summary of Parameters for Transit Subsidy Estimation

Parameter Value

Average vehicle occupancy rate 1.59 per vehicle

Costs per boarding $3.67 per boarding

Farebox recovery rate 50%3

Average daily downtown inbound transit ridership 87,7204

Source(s): King County Dept. of Transportation 2007; King County Dept. of Transportation 2008; Puget Sound

Regional Council 2009; Puget Sound Regional Council 2010; Seattle Department of Transportation 2003.

Using these parameters and the number of averted vehicle trips, the estimated additional

transit subsidy to support road pricing would be $61 million in 20125. In reality, the needed

subsidies may be considerably less, because increased level of ridership could result in higher

farebox recovery rate and lower marginal costs of providing transit service.

3 The fare box recovery rate, a ratio of fare revenues over operating costs, was 24.6% for the entire system in 2008; however, the

bus routes serving downtown Seattle have much higher recovery rates because of the shorter route lengths and higher ridership

levels particular during daytime when additional capacity is necessary for the road pricing program. For this reason, this study

assumes that the fare box recovery rate will be roughly 50%, which is a rate of several highest ridership routes. 4 73100/weekday * 20% growth (2005-2008) 5 Additional subsidy =Δ vehicle volume * average vehicle occupancy * cost per boarding * (1- farebox recovery rate)



IV. INDIRECT COSTS AND BENEFITS

Travel Time Savings

Travel time savings occur when consumers benefit from reduced travel times. The average travel

time is currently 0.55 hour per trip (PSRC 2009), and the estimated reduction from the lower

traffic volume would be 0.0137 hour, using the following algorithm:

PSRC (2009) indicates that the value of travel time is correlated to the wage rate of

passengers for private vehicles, plus the value of cargo for commercial vehicles.6 Using this

approach, PSRC (2009) estimates the value of time is $18.75 per hour for private vehicles, and

$50 per hour for commercial vehicles in Seattle.7 When multiplying the travel time savings by

the change in vehicle volume and value of time, the benefit of travel time savings will amount to

$77 million.

Travel Time Reliability

There are also benefits from improved travel time reliability; the reduced traffic volume lowers

the variations in travel time, which in turn causes further time savings as commuters have less

needs to budget additional time to avoid late arrival. Studies from London and Stockholm

suggest the reliability benefits be approximately one-third of the benefits of travel time savings

(Eliasson 2008; Santos and Fraser 2006). Assuming this relationship between travel time benefits

and reliability holds for Seattle, the value of travel time reliability will be $26 million.

Air Pollutants and Greenhouse Gasses

Each vehicle trip into the city center produces emissions from fuel combustion. These emissions

include greenhouse gasses (GHG), carbon monoxide (CO), nitrogen monoxide (NO), particulate

matter (PM), and volatile organic compounds (VOC). The emissions of these compounds

contribute to poor health conditions and climate change (IPCC 2007).

6 The approximate split between private and commercial vehicles is 75% private and 25% commercial

7 Texas Transportation Institute (2011) says the value of time for private vehicles is $16.30 per hour, and that for

commerce vehicles is $88.12.



Table 4 summarizes the current emissions levels of these pollutants (Puget Sound Clean

Air Agency 2008), percentage changes induced by road pricing, which are estimated from the

elasticities of the emission level of air pollutants to the changes in vehicle volume, and values for

monetization (Muller and Mendelsohn 2007; Muller et al. 2009; McCubbin and Delucchi 1999).

Table 4. Summary of Current Emission Levels, Estimated Changes, and Monetization Values

Parameters Current Emissions

(ton/year) Estimated Change

Value

(per ton)

GHG Emissions 2,682,559.47 -8.5% $27.0

CO Emissions 93,791.13 -9.8% $45.4

NO Emissions 11,579.71 -6.0% $81.0

VOC Emissions8 7,589.60 -8.6% $838.0

PM Emissions 205.67 -9.8% $7408.0

Source(s): Puget Sound Clean Air Agency 2008; Muller and Mendelsohn 2007; Muller et al. 2009; McCubbin and

Delucchi 1999.

Multiplying these parameters for each pollutant suggests the value of the lower emissions

amount to $7.17 million per year.

Traffic Accidents

The decrease in traffic volume is likely to lower the number of traffic accidents, which

deteriorate social welfare through property damages, injuries, or loss of life. Rotaris et al. (2010)

report that road pricing in London lowered traffic accidents by 3.6%. Using the elasticity of

traffic accidents to traffic volume change, the estimated drop in the number of accidents would

be 2.4%. With the baseline number of accidents in Seattle (King County Dept. of Transportation

2009)9 and monetization values (PSRC 2009) listed in Table 5, the reduced accidents would

improve the social welfare by $1.4 million per year.

8 Since data on the change in VOC is unavailable, the analysis uses average of the other computed percent changes

(approx. 8.5%). 9 The report shows the total number of accidents in King County, and the analysis assumes that one third of them

involve vehicles destined to/from downtown Seattle.



Table 5. Summary of Traffic Accidents Estimation and Monetization Values

Parameters Number of Incidents Estimated Change Value

(per accident)

Fatal 4 -2.4% $2,500,000

Non-fatal 590 -2.4% $75,500

Property damage only 595 -2.4% $2,600

Source(s): King County Dept. of Transportation 2009; PSRC 2009.

V. OTHER CONSIDERATIONS

Distributional Effects

Public policy often creates winners and losers, and these distributional effects tend to draw

criticism from the opponents of the policy. This study does not quantify them due to the

difficulties in quantification and redistribution, as recommended by Zerbe and Dively for most

policy options (1994), but qualitatively assesses the following three effects to see if they can

significantly affect the analysis results.

One effect is the potential decline in retail sales within the cordon, which could occur if

shoppers avoid downtown businesses because of the added travel costs. There have been several

studies on this effect, most notably the analysis by Quddus et al. (2005) on retail sales in London.

Quddus et al. (2005) compare the sales inside and outside the cordon before and after the

introduction of the road pricing with econometric analysis. They conclude that there were some

effects on particular franchises but no significant effect on the overall retail sales. Daunfeldt et al.

(2009) also find similar effects in Stockholm. Furthermore, since most weekday shoppers are

downtown workers, the toll should have minimal effect on their spending habits, and downtown

businesses may even benefit from road pricing due to the increased transit service and reduced

traffic congestion. These findings suggest that the potential adverse effects on retail sales within

the cordon are negligible.

The second potential effect is the reduced competitiveness of the freight industry. The

Port of Seattle is the eighth busiest port in the nation in cargo volume, and many of the container

terminals are located just south of the city center (Enghirst et al. 2011). The port faces

competition with other ports in the West Coast, including the Port of Tacoma located about 30



miles south of Seattle. It is possible that the road pricing in the city center will increase the costs

for freight trucks and shift the demand away from the Port of Seattle and local freight carriers.

Enghirst et al. (2011) however find that through GPS-survey, none of the port-related trucks

passes through the city center. Furthermore, the averted vehicle trips from road pricing would

alleviate the congestion on local roadways and thus may improve the freight mobility.

The last distributional effect in this discussion is the potential change in land use patterns.

As discussed earlier, road pricing is likely to reduce significant amounts of vehicles entering the

cordon. This translates into the reduced demand for parking spaces, which could lead to

redevelopment of commercial parking lots, particularly concentrated in the northern and southern

edges of downtown Seattle. In addition, changes in commute patterns may have distributional

effects on housing prices. These effects on land use, however, are unclear and controversial. On

one hand, European Federation for Transport and Environment (2003) and Banister (2002) argue

that road pricing in theory has minimal effects in citywide land use patterns. On the other hand,

land use modeling by Hargreaves and Echenique (2008) implicates potential displacement of

low-income population in or near the city center, and econometric analysis by Zhang and Shing

(2006) finds that the housing price just outside the cordon increased at higher rates than other

areas. However, Hargreaves and Echenique (2008) also note that increased level of transit

service can easily offset the adverse effects, and Zhang and Shing (2006) caution that the

causation of the housing price change is not clear and needs further assessment through long-

term observation. In sum, land use effects are too complex to predict and quantify, but even if the

effects are negative, it is possible to offset them through countermeasures such as increased level

of transit service.

Long-Term Effects

The long-term effects of road pricing are also controversial. Eliasson (2008) argues that the

traffic volume may return to the previous level after a certain period due to acclimatization effect,

a phenomenon that the effect of road pricing on driving behavior fades away as commuters

become accustomed to toll. Triple convergence, another phenomenon that freed-up road capacity

encourages people to drive more (Downs 2007), could also offset a portion of the traffic volume

decline if the lower level of traffic jam prompts some new transit riders to resume driving.

Eliasson (2008) however argues that these long-term effects are likely to be insignificant, since



his observation period for road pricing in Stockholm was long enough to capture these effects. In

fact, in London the traffic volume reduction remained stable for years until the toll rate changed

(Transport for London 2008). Furthermore, in contrast to the effect of acclimation and triple

convergence, the decline in traffic volume could become larger in the long run because road

pricing can alter the consumer behavior in housing choice and car ownership. For these reasons,

these long-term effects are unlikely to undermine the effects of road pricing.

Government Revenues

Various government entities, ranging from the federal government to the local transit agency,

will receive or lose some revenues from road pricing. One obvious example is the toll revenues

from road pricing itself, which would amount to $109 million per year in this analysis. Other

changes include additional transit fare revenues for transit agencies, fewer revenues from

commercial parking tax and metered parking fee for the city, and fewer gas tax revenues for the

state and federal government. These revenue changes are simply cash transfer between the

governments and residents; whereas it is possible that these excise taxes beyond socially optimal

point can compromise social welfare by overcompensating the negative externalities, the study

assumes that there will be no change in social welfare as in most benefit-cost analyses (Zerbe

and Dively 1994). Therefore, while it is important to recognize and quantify the changes in

government revenues for financial analysis, the magnitude of the changes does not affect the net

benefits for the region.

VI. RESULTS

The study sets the analysis period to thirty-years, a standard analysis period for infrastructure

projects. The key element in aggregating the benefits and costs is a discount rate, an instrument

to express future costs or benefits at today’s equivalent value. All benefit-cost analyses are

highly sensitive to a discount rate, and there have been various studies and recommendation on

the selection of a discount rate. For instance, the Congressional Budget Office (CBO 1998)

recommends a rate of 2% while the Office and Management and Budget (OMB 1992) suggest its



upper bound be 7%. Zerbe and Dively (1994) recommend a more moderate rate ranging from

2.5% to 5.5%. For previous road pricing studies, Eliasson (2008) uses a rate of 4% for his

Stockholm analysis, and Santos and Fraser (2006) use a rate of 3.5% for their London analysis.

This analysis first uses a rate of 5% as discussed earlier, but later tests other rates in sensitivity

analysis.

In addition to this discounting, the projected population growth requires the adjustment of

the benefits and costs accordingly.10

It also assumes that the benefits and costs related to fuel use

would decrease with improving fuel economy, and that the value of time and labor costs would

increase with personal income growth. The costs of toll, driving, fuel, capital replacement, and

monetization values will grow at the rate of inflation, but the discount rate of 5% internalizes

these changes.

Table 6. Discount Rate and Growth Factors

Parameters Rate

Discount rate 5.00%

Population growth 1.30%

Fuel efficiency growth 1.25%

Personal income growth 1.45%

Source(s): Bureau of Transportation Statistics 2011; Washington State Office of Financial Management 2011.

Table 7 shows the discounted costs and benefits over the thirty-year analysis period with

the level debt-service financing option. When aggregated, the net benefits are positive at $585

million in present value, showing that road pricing in downtown Seattle would have positive

impacts on the area.

Table 7. Discounted Benefits and Costs over Thirty-year Period

Discounted Costs Discounted Benefits

Capital costs $357,459,493 Travel time savings $1,987,258,411

Operation costs $802,829,103 Travel time reliability $662,419,470

Transit subsidy $1,038,042,253 Lower GHG emissions $89,862,081

Air quality improvement $19,802,735

Fewer traffic accidents $24,098,531

NPV Costs $5,251,990,677 NPV Benefits $5,837,101,056

NPV Net Benefits $585,110,379

10

The capital replacement portion of the operating cost, assumed to be about half, is not inflated while the labor

portion is inflated at income growth rate.



Finally, while the analysis period is thirty-year, the results find that the benefits will begin to

exceed the costs after the ninth year of implementation. This implies that it is likely that the

project would result in net benefits even if it lasts significantly less than thirty years.

VII. SENSITIVITY ANALYSIS

The uncertainty of various parameters, particularly the price elasticity, toll rate, and discount rate,

requires extensive sensitivity analysis. Monte Carlo simulation can test the sensitivity of the

results over various parameters at one time (Mooney 1997). This simulation incorporates

information about the range and certainty of the estimates by expressing parameters with

probability distributions rather than with single point estimates. It then tests a large number of

possible values for each parameter and draws a distribution of possible outcomes. This

distribution gives a better picture of the possible benefits of the future than a single point

estimate can.

Table 8 summarizes the varied parameters with their plausible range and certainty. The

simulation uses normal distribution for parameters found through real-world observation, and

uniform distribution on other parameters.

Table 8. Summary of Parameters for Monte Carlo Simulations

Parameters Distribution Parameters

Discount Rate Uniform Min: 0.035, Max:0.080

Trip Costs Normal Mean:$6.40, Std. Dev: $0.64

Toll Rate Uniform Min: 2, Max: 3

Elasticity of Trips Uniform Min: -0.6, Max: -0.4

Capital Costs Normal Mean: $362,000,000, Std. Dev: $72,400,000

Operation Costs Normal Mean: $38,900,000, Std. Dev: $7,780,000

Fuel Efficiency Growth Rate Normal Mean: 1.25%, Std. Dev: 0.125%

Annual Income Growth Rate Normal Mean: 3.10%, Std. Dev: 0.310%

Annual Population Growth Rate Normal Mean: 1.30%, Std. Dev: 0.130%



Figure 4 shows the results of the simulation with these parameters for 100,000 trials; in

most cases, the net benefits are positive, and the expected net present value is $824 million.

Figure 4. Results of Monte Carlo Simulation

The study also uses traditional sensitivity analysis to test the importance of three crucial

parameters in the model: the toll rate, price elasticity of trips, and discount rate. Figure 5 shows

how the net benefits in present value change for different values of these parameters. While the

results are highly sensitive to all three variables, even in the conservative scenarios the predicted

benefits will be positive.



Figure 5. Summary of Sensitivity Analysis

VIII. CONCLUSION

The expected growth of the region is likely to increase traffic congestion in Seattle in the coming

decades (PSRC 2010). A policy solution is necessary to address traffic congestion and its

negative externalities for healthy growth of the metro area. After considering numerous benefits

and costs, this analysis indicates that cordon-based road pricing in Seattle can significantly lower

its traffic volume and result in better social welfare. Shorter travel time and better reliability are

the major contributors to this positive outcome, but the secondary benefits such as fewer harmful

emissions and traffic accidents also play significant roles in improving the welfare.

Despite using the best available information in determining the net benefits in present

value, the study uses a number of assumptions to predict the impacts. The elasticity-based

modeling approach itself is one of the major limitations of the study, and more sophisticated

origin-destination traffic modeling (OD model) will provide better information on the impacts of

road pricing, particularly on traffic volume. However, an important policy implication from the

extensive sensitivity and uncertainty analysis is that road pricing is very likely to have positive

net benefits even in conservative scenarios. This benefit-cost analysis therefore successfully

demonstrates that road pricing can play a crucial role in improving social welfare in the region

and enabling the city to achieve healthy growth.

0

200

400

600

800

1,000

1,200

1,400

$2.0 $2.5 $3.0 -0.4 -0.5 -0.6 3.5% 5.3% 7.0%

Mill

ion

do

llar

Toll Rate Discount Rate Elasticity



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