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Journal of the American Planning Association
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Getting the Prices Right
Gregory Pierce a & Donald Shoup a
a Department of Urban Planning , University of California , Los Angeles
Published online: 09 May 2013.
To cite this article: Gregory Pierce & Donald Shoup (2013): Getting the Prices Right, Journal of the American Planning
Association, 79:1, 67-81
To link to this article: http://dx.doi.org/10.1080/01944363.2013.787307
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67
Problem, research strategy, and
fi ndings: Underpriced and overcrowded
curb parking creates problems for everyone
except a few lucky drivers who fi nd a cheap
space; all the other drivers who cruise to
fi nd an open space waste time and fuel,
congest traffi c, and pollute the air. Over-
priced and underoccupied parking also
creates problems; when curb spaces remain
empty, merchants lose potential customers,
workers lose jobs, and cities lose tax
revenue. To address these problems, San
Francisco has established SFpark, a pro-
gram that adjusts prices to achieve avail-
ability of one or two open spaces per block.
To measure how prices affected on-street
occupancy, we calculated the price elastic-
ity of demand revealed by over 5,000 price
and occupancy changes during the pro-
gram’s fi rst year.
Price elasticity has an average value of
–0.4, but varies greatly by time of day,
location, and several other factors. The
average meter price fell 1% during the fi rst
year, so SFpark adjusted prices without
increasing them overall. This study is the fi rst
to use measured occupancy to estimate the
elasticity of demand for on-street parking. It
also offers the fi rst evaluation of pricing that
varies by time of day and location to manage
curb parking.
Takeaway for practice: San Francisco
can improve its program by making drivers
more aware of the variable prices, reducing
the disabled placard abuse, and introducing
seasonal price adjustments. Other cities can
incorporate performance parking as a form
of congestion pricing.
Keywords: performance parking, price
elasticity of demand, optimal pricing
Research support: University of Califor-
nia Transportation Center.
Getting the Prices Right
An Evaluation of Pricing Parking by Demand in
San Francisco
Gregory Pierce and Donald Shoup
In 2011, San Francisco adopted the biggest price reform for on-street
parking since the invention of the parking meter. Oklahoma City installed
the world’s fi rst parking meters in 1935, charging 5 cents an hour (85
cents in 2013 currency). Most cities’ pricing policies have changed little since
then. Parking meters usually charge the same price all day, and some cities
charge the same price everywhere.1 San Francisco has moved toward a more
effi cient and equitable system of on-street parking prices that vary by time of
day and from block to block.
Is this a good thing? In principle, absolutely. SFpark, San Francisco’s
new pricing program, incorporates long-established theoretical principles for
the optimal pricing of public services. Nobel-prize economist William
Vickrey, a visionary on many public pricing topics, recommended variable
prices for on-street parking as long ago as 1954. He proposed that curb-
parking prices should be set “at a level so determined as to keep the amount
of parking down suffi ciently so that there will almost always be space avail-
able for those willing to pay the fee” (Vickrey, 1954, p. 64).2 The primitive
metering technology in 1954 made Vickrey’s proposal to match prices to
demand appear outlandish, and it became one of what he called his
“innovative failures in economics” (Vickrey, 1993, p. 1).3
When using prices to manage transportation demand, Philip Goodwin
(2001, p. 29) distinguished between two strategies. The fi rst was to “get the
prices right: where travel is currently undercharged, getting the price right will
reduce traffi c.” The second was “let’s decide how much traffi c we want, and
then use prices to achieve it” (p. 29). These two strategies have been called the
price and quantity approaches to dealing with externalities, where individual
decisions fail to account for spillover effects.4 Setting a target occupancy rate
for curb parking represents the second approach; for a typical block, this
means aiming for at least one open space on each side of the street. Rather
than choosing the right price for curb parking, planners adjust prices to reach
the right occupancy rate.
About the authors:
Gregory Pierce (gspierce@ucla.edu) is a
doctoral student in the Department of
Urban Planning at the University of Califor-
nia, Los Angeles. Donald Shoup, FAICP
(shoup@ucla.edu), is distinguished professor
in the Department of Urban Planning at the
University of California, Los Angeles.
Journal of the American Planning Association,
Vol. 79, No. 1, Winter 2013
DOI 10.1080/01944363.2013.787307
© American Planning Association, Chicago, IL.
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68 Journal of the American Planning Association, Winter 2013, Vol. 79, No. 1
Distorted prices are either too high or too low. In
analyzing the city as a distorted-price system, Wilbur
Thompson (1968) argued that the failure to use prices in
the public sector is the root of many urban problems, using
on-street parking as an example: “Rationing need not
always be achieved with money, as when a motorist circles
the block over and over looking for a place to park….The
parking ‘problem’ may be reinterpreted as an implicit
decision to keep the money price artifi cially low (zero or a
nickel an hour at a meter) and supplement it with a waiting
cost or time price” (p. 29). This waiting cost is the time
drivers spend circling the block searching for an open space.
The parking price that achieves one or two open spaces
per block is not a free-market price; it is instead a public
price for a public service, and it should be set to achieve
the public goal of effectively managing the parking supply.
Because cities can charge parked cars more easily than
moving cars, getting the prices right for curb parking is a
cheaper version of congestion pricing for traffi c.
In this article, we fi rst review the problems caused by
mispriced curb parking. We next explain how San Francisco
aims to set the right prices for curb parking by establishing a
target occupancy rate. We then analyze the data on changes
in occupancy rates after more than 5,000 price changes to
learn how parking prices affected occupancy during SFpark’s
fi rst year. While endorsing many of the details of SFpark, we
conclude by suggesting ways to improve it.
The Problem of Cruising for Curb
Parking
Scholars have clearly established the conceptual basis
for cities to treat curb space as a valuable commodity rather
than a free good (Arnott & Inci, 2006; Klein, Moore, &
Reja, 1997; Shoup 2011; Vickrey, 1954, 1994). They
generally conclude that cities should set the right prices for
curb parking because the wrong prices do so much harm.
Where curb parking is underpriced and overcrowded,
drivers cruise the streets hoping to fi nd an open space. This
cruising greatly increases traffi c congestion: Ten studies
conducted in eight cities between 1927 and 2011 found
that an average of 34% of cars in congested downtown
traffi c were cruising for parking (Table 1). In 2007, for
example, researchers interviewed drivers stopped at traffi c
signals in New York City and found that roughly one third
were cruising. Another study in a 15-block commercial
district in Los Angeles estimated that cruising for curb
parking created nearly 1.5 million excess vehicle kilometers
of travel per year, equivalent to 38 trips around the earth or
four trips to the moon (Shoup, 2011, Chapter 14).
Underpriced parking creates large social costs for
everyone except a few lucky drivers who happen to fi nd a
cheap space. Overpriced parking also causes problems;
when curb spaces remain empty, nearby stores lose poten-
tial customers, employees lose jobs, and governments lose
tax revenue. To avoid the problems caused by mispriced
parking, some cities, including San Francisco, Seattle, and
Washington, DC, have begun to adjust their curb-parking
prices by location and time of day. The process of adjusting
prices based on occupancy has been called demand-based
or performance-based pricing. This pricing policy can
improve the performance of both curb parking and the
adjacent roads.
The Advantages of Performance-
Parking Prices
San Francisco has embarked on an ambitious program,
called SFpark, to get the price of curb parking right.5 The
U.S. Department of Transportation sponsored SFpark with
an $18 million grant from its Value Pricing Pilot Program
to test “demand-responsive pricing to manage parking
towards availability targets, enhanced parking regulation
enforcement, and new parking information systems” (see
the USDOT’s website for its Tolling and Pricing Program,
http://ops.fhwa.dot.gov/tolling_pricing/value_pricing/
projects/not_involving_tolls/parking_pricing/ca_
sfpark_sf.htm).
In seven pilot zones, San Francisco has installed
sensors that report the occupancy of each curb space on
every block and parking meters that charge variable
prices according to the time of day. Using this new
Table 1. Studies of cruising for curb parking.
Year City
Share of traffi c cruising
(%)
1927 Detroit, MI 19
1927 Detroit, MI 34
1960 New Haven, CT 17
1977 Freiburg, Germany 74
1985 Cambridge, MA 30
1993 New York, NY 8
2005 Los Angeles, CA 68
2007 New York, NY 28
2007 New York, NY 45
2011 Barcelona, Spain 18
Average 34
Source: Shoup (2011, p. 290).
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Pierce and Shoup: An Evaluation of Pricing Parking by Demand 69
technology, the city adjusts parking prices in response to
the occupancy rates about once every six weeks. This
trial-and-error process aims to create a structure of
prices that vary by time and location to produce an
average occupancy rate of between 60% and 80% on
every block.
Consider the prices of curb parking on a weekday at
the well-known tourist destination, Fisherman’s Wharf, in
May 2012 (Figure 1). Each block has different prices
during three periods of the day (before noon, from noon to
3 p.m., and after 3 p.m.). Before the fi rst changes in Au-
gust 2011, the price was $3 an hour at all times. By May
2012, prices on almost every block had declined for the
period before noon, while most prices had increased be-
tween noon and 3 p.m. Most prices after 3 p.m. were lower
than during mid-day, but higher than in the morning. The
price of parking on the block on the far left of the maps in
Figure 1, for example, was $1.50 an hour before noon,
$3 an hour from noon to 3 p.m., and $1.75 an hour after
3 p.m. A driver who arrived at 11 a.m. and parked for two
hours thus paid $1.50 for the fi rst hour and $3 for the
second hour.
SFpark based these price adjustments purely on
observed occupancy. Planners cannot predict the right
price for parking on every block at every time of day, but
they can use a simple trial-and-error process to adjust
prices in response to occupancy rates. Figure 2 illustrates
how nudging prices up on crowded block A and down on
underoccupied block B can shift only one car to improve
the performance of both blocks.
Will Performance Prices Change Drivers’
Behavior?
Using prices to change the behavior of only a few
parkers can open up one or two spaces on every block. By
reducing the need to cruise for curb parking, this small
change will provide large benefi ts for almost everyone. As
Stanford University professor Balaji Prabhakar commented
about small policy changes that produce large benefi ts,
“This is one of the nicer problems. You don’t have to
change everyone’s behavior; in fact, it’s better if you don’t”
(Markoff, 2012, p. D1).
Nudging the price up on an underpriced, over-
crowded block provides several important benefi ts. First,
creating one or two open spaces will save time that driv-
ers previously spent cruising. Shoup (2011) found that,
in a single year, drivers wasted 100,000 hours while
cruising for underpriced curb parking in a 15-block
business district in Los Angeles. Second, if fewer cars are
cruising, both drivers and bus passengers will save time in
less congested traffi c. Third, if prices are higher, drivers
will park for a shorter time, increase the turnover rate,
and thus enable more cars to use the curb spaces. Fourth,
some people will carpool when meter rates increase, so
more customers will arrive in the cars that park at the
curb. Using prices to change only a few parkers’ behavior
can thus improve transportation, the economy, and the
environment.
Beyond managing the on-street supply, SFpark helps to
depoliticize parking by stating a clear principle for setting
the prices for curb spaces. San Francisco charges the lowest
prices possible without creating a parking shortage. Relying
on transparent, data-based rules to set prices makes an end
run around the usual politics of parking prices (Table 2).
Demand sets the prices for parking, and wanting more
revenue no longer justifi es raising prices.
Figure 1. Parking prices on a weekday at Fisherman’s Wharf in May 2012.
(Color fi gure available online.)
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70 Journal of the American Planning Association, Winter 2013, Vol. 79, No. 1
First Movers
If higher prices encourage a few parkers to move away
from the most crowded blocks, who will move fi rst?
Three types of drivers are most likely to park farther
away: long-term parkers, solo drivers, and those who
place a low value on saving travel time. (Shoup’s [2011]
chapter 18 presents a model of how parking prices affect
location choices.)
Vickrey (1954) noted that if prices are set to create an
open space on every block, “there would be an incentive for
each parker to park as far as possible in locations where the
demand is light, and there will be a natural tendency for the
long-term parkers to park somewhat farther away from the
areas of heaviest demand” (p. 64). Long-term parkers have
more to gain from moving to cheaper curb spaces. A driver
who parks for four hours in a distant space that costs $1 an
hour less will save $4, while a driver who parks for 15 min-
utes would save only 25 cents. It therefore seems likely that
drivers who park for a longer time will be among the fi rst to
move to the cheaper but less convenient spaces. If someone
who parks for four hours shifts to a distant space, several
drivers who each park for a shorter time can use the more
convenient space and save walking time.
Solo drivers will also have more to gain from shifting
to cheaper curb spaces. A solo driver who parks for an hour
Figure 2. Performance prices create open spaces on every block.
(Color fi gure available online.)
Table 2. Prices change according to occupancy rates in the previous period.
Occupancy rate Price change
Below 30% –50 cents per hour
30%–60% –25 cents per hour
60%−80% no change
Above 80% +25 cents per hour
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Pierce and Shoup: An Evaluation of Pricing Parking by Demand 71
and shifts to a more distant space that costs $1 an hour less
will save $1, while a four-person carpool will save only
25 cents per person. Therefore, it seems likely that solo
drivers will be among the fi rst to move to the cheaper but
less expensive spaces, while carpoolers will park in the more
convenient but more expensive spaces.
Drivers who enjoy walking or who place a low value
on saving time spent walking will also shift toward the
cheaper spaces. For example, drivers who arrive early and
have time to spare will park farther away, while drivers who
arrive late will park closer. Lower-income drivers who place
a lower value on saving time are also more likely to park
farther away. If parking prices remain the same everywhere,
lower-income drivers cannot save money by shifting their
parking locations and walking farther.
SFpark thus allocates parking spaces more effi ciently
than uniform prices can. Short-time parkers, carpoolers,
those who have diffi culty walking, and those who place a
high value on saving time will shift toward the more
convenient parking spaces. In contrast, long-time parkers,
solo drivers, those who enjoy walking, and those who
place a low value on saving time will shift toward the
more distant parking spaces. SFpark will give all drivers a
new opportunity to save money or time, which should
benefi t everyone.
Did SFpark Change Drivers’ Behavior
in the Right Direction?
Following several years of planning, the San Francisco
Municipal Transportation Authority (SFMTA) launched
SFpark in April 2011 by installing new parking meters and
extending or removing the time limits on curb spaces. The
pilot program covers seven zones that contain 7,000 me-
tered curb spaces and 14 public garages. The initial prices
in each zone simply carried over from the previous, uni-
form pricing scheme. SFpark made the fi rst price changes
at the block level in August 2011.
Most meters operate daily from 9 a.m. to 6 p.m., with
prices that vary by the time of day and between weekdays
and weekends.6 SFMTA established the desired target
occupancy rate for SFpark blocks at between 60% and
80%. If average occupancy for a given period falls in this
range, the price will not change in the following period.
Otherwise, prices change based on occupancy rates in the
preceding period according to the schedule in Table 2. The
minimum price per hour on any block is 25 cents and the
maximum is $6. San Francisco’s pricing policy is thus
data-driven and transparent, while most other cities’
pricing policies are political and opaque.
In setting a target occupancy rate, SFpark has two
goals. First, curb parking will be readily available if one or
two spaces are open on every block; this will prevent
cruising and ensure that customers have easy access to
adjacent businesses. Second, curb parking will be well used
because most spaces are occupied; they will deliver as many
customers as possible to the adjacent businesses. The
greater the unpredictability of parking demand, the greater
the confl ict becomes between the two goals.
Raising the meter rates to ensure at least one vacant
space most of the time will reduce the average occupancy
rate. For example, large groups gathering for lunch at a
restaurant may generate exceptionally high parking demand
on a block on some days, so cities cannot aim for a consist-
ently high occupancy rate of 80%–90% without often
reaching 100% occupancy. Fully occupied curb parking
produces unwanted cruising, while a low average occupancy
means fewer customers. San Francisco set the target
occupancy rate at between 60% and 80% to deal with the
stochastic variation in parking demand and to balance the
competing goals of reliable availability and high occupancy.
If SFpark works as intended, prices will move occu-
pancy rates toward the target range. So how did prices
affect occupancies during the fi rst year of the program? To
answer this question, we can examine how the 5,294 price
changes during SFpark’s fi rst year affected occupancy rates
in the subsequent periods.
The Data
SFpark made six price adjustments during the fi rst year
(Table 3). Prices increased in 32% of the cases, declined in
31%, and remained the same in 37%, with almost no
change in the average price. There was, however, a pro-
nounced spatial pattern to the changes.
Prices rose during all periods for the downtown area,
but fell during all periods in the Civic Center, Fisherman’s
Wharf, and South Embarcadero. In the other areas, prices
rose during some periods and fell during others. On aver-
age, prices declined in the morning and increased in the
midday and afternoon. The average price fell 1% during
the fi rst year, so SFpark adjusted prices up and down
according to demand without increasing prices overall.
Before each price change, SFpark publishes data on the
occupancy and prices for all curb spaces in the pilot zones.7
The price elasticity of demand measures how these price
changes affected occupancy rates. Price elasticity is defi ned
as the percent change in the occupancy rate (the quantity
parking demanded) divided by the percent change in the
meter price. For example, if a 10% price increase leads to
a 5% fall in occupancy, the price elasticity of demand is
–0.5 (= –5% ÷ 10%).
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72 Journal of the American Planning Association, Winter 2013, Vol. 79, No. 1
Using data from parking meters in Seattle, Ottosson
Chen, Wang, and Lin (2013) calculated the price elasticity
of demand for on-street parking by time of day at the
block level. Because the authors did not have data on
parking occupancy, however, they inferred occupancy from
the meter payment data. Our study is the fi rst to use
measured occupancy to estimate the elasticity of demand
for on-street parking.
We illustrate the price elasticity of demand for curb
parking by referring to the results of two SFpark price
changes reported in the New York Times (Cooper &
McGinty, 2012). Figure 3 shows the price and occupancy
changes at two locations: the 600 block of Beach Street at
Fisherman’s Wharf and the 200 block of Drumm Street in
Downtown. On Beach Street, the initial price in August
2011 was $3 an hour and the initial occupancy only 27%.
By February 2012, the price had decreased to $1.75 an
hour, while occupancy had increased to 56%. Because
occupancy rose by 70% after the price fell by 53%, the
elasticity of demand was –1.3.8 Meter revenue rose after
the price fell because demand was elastic: Higher occu-
pancy more than offset the lower price. In this case,
SFpark produced lower prices, higher occupancy, and
more revenue.
On Drumm Street, the initial price was $3.50 an hour
and the initial occupancy was 98%. After the price increased
to $4.50 an hour, occupancy decreased to 86%. The price
elasticity of demand was –0.5 because occupancy fell by
13% after the price rose by 25%. Meter revenue increased
when the price increased because demand was inelastic:
Occupancy decreased by less than the price increased.
The price changes moved occupancy toward the
desired goal and increased total revenue on both Beach and
Drumm Streets. Nevertheless, given the target occupancy
range of 60% to 80%, the price remained too low on
Beach (where occupancy was only 56%) and too high on
Drumm (where occupancy was 86%). This result likely
occurred because prices change slowly with each
adjustment (up by no more than 25 cents an hour and
down by no more than 50 cents an hour), and the program
had operated for only six months. The schedule of price
adjustments may be too gradual in such cases.
The Results
We calculated the elasticity of demand revealed by
5,294 price changes during SFpark’s fi rst year. For each
price change, we compared the old price and the average
occupancy during the previous six weeks to the new price
and the average occupancy during the next six weeks. We,
thus, have 5,294 elasticity measurements, one for each
Table 3. Average curb-parking prices in pilot zones on weekdays.
August 2011 August 2012
Neighborhood
All day
($)
Before noon
($)
Noon to 3 p.m.
($)
After 3 p.m.
($)
Average
($)
Change
(%)
Downtown 3.50 3.92 4.51 4.40 4.28 22
South Embarcadero 3.50 2.47 3.16 2.83 2.82 –19
Civic Center 3.00 1.87 2.87 2.56 2.43 –19
Fisherman’s Wharf 3.00 1.51 2.82 2.59 2.31 –23
Fillmore 2.00 1.88 2.44 2.36 2.23 11
Marina 2.00 1.91 2.72 2.68 2.44 22
Mission 2.00 1.73 2.50 2.63 2.29 14
Average 2.71 2.18 3.00 2.86 2.68 –1
Figure 3. Pricing parking by demand.
Source: Cooper and McGinty, 2012. Reprinted with permission from
the New York Times.
(Color fi gure available online.)
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Pierce and Shoup: An Evaluation of Pricing Parking by Demand 73
price change during the year at each time of day and at
each location. The data show that the price elasticity of
demand for curb parking is far from uniform. Elasticity
varies according to location, time of day, day of the week,
initial price, and date of the price change. The data also
show astonishing variation in the price elasticity of demand
at the block level.
Elasticity Varies by Location. Figure 4 shows that the
average price elasticity varies considerably across the seven
pilot zones of SFpark, from –0.53 at Fisherman’s Wharf to
–0.21 in the Mission District. The greatest disparity
appears between the mostly residential Mission and Marina
zones, which are the least elastic and therefore respond least
to price changes, and the predominantly commercial and
offi ce zones that are most elastic and respond the most to
price changes.
Elasticity Varies by Time of Day and Day of Week.
Figure 5 shows that the price elasticity also varies by time of
day and day of the week. Demand is less elastic in the morn-
ing than in the midday and afternoon, perhaps because many
trips in the morning are to work and school while more trips
later in the day are made for leisure purposes. Demand is also
less elastic on the weekend than on weekdays.9
Elasticity Varies by Initial Price. Figure 6 shows that
the elasticity also varies according to the initial price of
parking before a price change. The price elasticity of
demand for the cheapest parking (between $0 and $1) is
very low. Elasticity increases as price rises until it reaches
$4, and then declines.
Elasticity Varies by the Size of the Price Change.
SFpark adjusts prices in only three increments: ⫹25 cents,
–25 cents, or –50 cents an hour. Figure 7 shows that the
greatest elasticity occurs after the largest price change, a
reduction of 50 cents an hour. For price changes of
25 cents an hour, customers reacted more strongly to price
increases than to price decreases, a phenomenon often
observed in other markets (for example, see Kalyanaram
and Winer, 1995; Thaler, 1985).
Elasticity Varies Over Time. Figure 8 shows the price
elasticity of demand for parking in response to each of the
fi rst six price changes of the pilot program. The absolute
value of elasticity was small after the fi rst price change,
increased dramatically after the second, and then declined
following subsequent price changes.
Two factors may explain the small positive elasticity
after the fi rst price change. First, many drivers probably
had not heard about SFpark when the fi rst price changes
occurred in August 2011. If so, they were unaware of the
lower prices available to those who were willing to walk
farther from their parking spaces to their destinations.
More drivers may have learned about SFpark after the
Figure 4. Elasticity by location.
(Color fi gure available online.)
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74 Journal of the American Planning Association, Winter 2013, Vol. 79, No. 1
Figure 5. Elasticity by time of day and day of the week.
(Color fi gure available online.)
Figure 6. Elasticity by initial price.
(Color fi gure available online.)
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Pierce and Shoup: An Evaluation of Pricing Parking by Demand 75
second price change in October. Thus, those most willing
to shift their parking locations to save money may have
moved from expensive blocks to cheaper blocks to take
advantage of the new options SFpark made available.
After subsequent price changes, drivers who could save
the most from changing their parking patterns had prob-
ably already done so, which helps to explain the declining
elasticity.
A second reason for the small response after the fi rst
price change is that many factors other than price affect
parking demand and supply (for example, seasonal varia-
tions, street closures, construction projects, and parking
bans for special events like parades). Therefore, if the
price changes had little effect on demand in August 2011,
all these other factors may have swamped the response to
price changes.
Elasticity Varies Greatly After Individual Price
Changes. The previous calculations refl ected the average
elasticities of demand for price changes at different locations,
times of day, initial prices, sizes of price changes, and dates.
These average elasticities varied over a wide range of values,
from ⫹0.05 to –0.98 (Figure 8). When we plot the elasticity
of demand for individual price changes at the block level, we
fi nd astonishing variety. Figure 9 shows the distribution of
the price elasticities calculated for 5,294 individual price and
occupancy changes on 1,492 city blocks.
The wide range of price elasticities suggests, as one
would expect, that many variables other than price affect
parking demand. In many cases, the price elasticity was
positive, which means that occupancy either rose after
prices rose or fell after prices fell. Higher prices do not
cause higher occupancy and lower prices do not cause
lower occupancy, so other factors must have overwhelmed
the effects of prices on occupancy in the cases of positive
price elasticity. The wide range of elasticity at the block
level also suggests that the circumstances on individual
blocks vary so greatly that planners will never be able to
develop a robust theoretical model to predict the correct
prices needed to achieve the target occupancy for every
block. Instead, the best way to achieve target occupancy is
to do what SFpark does: Adjust prices in response to the
observed occupancy. This simple trial-and-error method
mirrors how other markets establish prices, so it should
also work in the market for on-street parking.
We can further illustrate the diffi culty of predicting
the right price of parking by examining the variation in
price elasticity of demand in the Civic Center on weekday
mornings during the fi rst year of SFpark. Table 4 shows
the 10 city blocks with the largest range of elasticity. All
are located within a short walk from City Hall.10 Yet, even
on the same block and at the same time of day, elasticity
varies greatly.
For instance, on the 200 block of Van Ness Avenue the
initial average occupancy was 33% on weekday mornings.
After the price fell from $3.00 to $2.75 an hour, occupancy
rose to 47%, yielding a price elasticity of –4.0. In the subse-
quent period, even though the price dropped to $2.50 an
Figure 7. Elasticity by size of the price change.
(Color fi gure available online.)
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76 Journal of the American Planning Association, Winter 2013, Vol. 79, No. 1
Figure 8. Elasticity over time.
(Color fi gure available online.)
Figure 9. Distribution of elasticities for 5,294 price changes.
(Color fi gure available online.)
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Pierce and Shoup: An Evaluation of Pricing Parking by Demand 77
hour, occupancy fell to 20%, yielding an elasticity of ⫹8.5.
Powerful factors other than price must have infl uenced
demand on this block. Because demand is clearly site-and-
time specifi c, there is no way to measure the aggregate
demand for curb parking and no way to set the right prices
other than by aiming for the right occupancy.
Have the Occupancy Rates Moved Toward
the Goal?
Occupancy data in the fi rst year of the program sug-
gest that SFpark has made considerable progress toward
solving the important problems of severe overcrowding on
some blocks and very low occupancy on others. Table 5
shows that, on severely under- and overoccupied blocks
(those with initial occupancy rates below 30% or above
90%), the price changes tended to move occupancy in the
right direction in the subsequent period. Occupancy on
the underoccupied blocks rose after two thirds of the price
decreases, and occupancy on the overcrowded blocks fell
after two thirds of the price increases.
Removing the Obstacles to
Performance Pricing
SFpark has moved occupancy rates in the right direc-
tion, but this is only the beginning. SFpark can do more to
Table 4. Blocks with largest elasticity range in Civic Center on weekday
mornings.
Block Minimum Maximum Range
200 Van Ness Avenue –4.0 8.5 12.5
200 Franklin Street –3.6 5.6 9.2
400 Van Ness Avenue –4.4 4.6 9.0
100 Redwood Street –8.5 0.1 8.6
100 Hickory Street –1.0 6.9 7.9
500 Franklin Street –2.4 2.8 5.2
100 Van Ness Avenue –2.5 2.6 5.1
0 Larkin Street –2.9 1.7 4.6
100 Larkin Street –1.5 3.0 4.5
100 Franklin Street –3.7 0.8 4.5
provide information to drivers, to prevent abuse of disabled
placards, and to demonstrate the equity of the program.
Information About Performance Prices
Because parking prices and availability can vary greatly
within a short distance, drivers need real-time information
on prices and availability to park in the optimal spots. (If
SFpark achieves its goal of open parking spaces on every
block, drivers can choose parking location only by price.)
On its website, SFpark publishes maps that show the price
and availability of parking on every block at each time of
day (as in Figure 1), and it makes the same information
available on smart phones. In addition, anyone can enroll
to receive email messages from SFpark when prices change.
Nevertheless, many drivers, especially tourists, remain
unaware of these price variations and thus miss the oppor-
tunity to save money by walking a few blocks from their
cars to their destinations. If most drivers do not know that
parking prices vary by location and time of day, SFpark will
not easily achieve the desired one or two open spaces on
each block.
Many drivers may think it is not worth the effort to
research parking prices to get the best deal possible. These
drivers are not irrational, but rather are displaying what
economists call rational inattention (for example, see
Wiederholt, 2010). Parking for a short time does not cost
much, and drivers who automatically park close to their
destinations without thinking hard about prices are not
necessarily making bad choices. Instead, they are saving
time and energy by taking advantage of the open spaces
they see, demonstrating their inelastic demand for parking.
Everyone buys some things without doing the research
necessary to learn about all the cheaper or better
alternatives.
SFpark aims to improve parking and transportation,
not to ensure that every driver achieves the optimal
combination of cost and convenience when choosing a
parking space. Nevertheless, SFpark provides more
information about on-street parking prices than is available
about the geography of prices for almost anything else in
the city. Parking also makes a lively topic of conversation,
which is another way to learn about prices. Consequently,
most drivers who park frequently in an area will learn
which blocks are cheaper and which are more expensive.
Even if only a few parkers learn that they can save money
by walking farther, small changes by these parkers can
produce a few open spaces everywhere (see Figure 2). By
reducing the need to cruise for scarce curb parking, SFpark
can thus save time for parkers, reduce congestion, speed up
public transit, and improve transportation for almost
everyone.
Table 5. Improvement in the occupancy rates on under- and
overoccupied blocks.
Initial occupancy rate
Blocks with improved occupancy
rates after price change (%)
Below 30% 67
Above 90% 68
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78 Journal of the American Planning Association, Winter 2013, Vol. 79, No. 1
Although SFpark makes the parking market more
effi cient, it cannot guarantee that everyone will choose the
optimal parking space. Technology is advancing rapidly,
however, and automobile guidance systems can easily
incorporate pricing data from SFpark (SFpark encourages
people to develop apps and software using their data at
http://sfpark.org/how-it-works/open-source-data/). Drivers
may soon be able to input their destinations, the length of
time they want to park, and how much they value time
spent walking from their parking spaces to their
destinations. When they approach their destinations,
the guidance systems will give them turn-by-turn voice
directions to the optimal curb or off-street parking space.
The system will then show the best walking route to and
from their destination. As communications systems
become cheaper and easier to use, more drivers will use
fi ner-grained information to make better transportation
and parking choices. When that time comes, occupancy
rates will respond more quickly to curb-parking prices, and
SFpark will come closer to achieving its goals.
SFpark is a work in progress, but the information it
produces may eventually convert curb parking from a frus-
trating source of congestion and pollution into one of the
most effi cient transportation markets in the 21st century.
Disabled Placard Abuse
The staff of SFpark report that widespread abuse of
disabled parking placards helps to explain why occupancy
does not reliably respond to price changes. California
allows all drivers with disabled placards to park free for an
unlimited time at parking meters, so higher prices increase
the temptation to abuse placards. Raising prices on
crowded blocks may simply drive out paying parkers and
make more spaces available for placard abusers. If so,
prices will not reduce occupancy, and the price elasticity of
demand will remain artifi cially low.
Reforms in other states show how California can
prevent placard abuse at parking meters. In 1995,
Michigan adopted a two-tier placard system that takes into
account different levels of disability. Drivers with severe
disabilities receive special placards allowing them to park
for free at meters. Drivers with less severe disabilities re-
ceive ordinary placards and must pay (Michigan Secretary
of State, 2011). Before this reform, Michigan had issued
500,000 disabled placards that allowed all users to park
free at meters. After the state enacted its two-tier reform,
only 10,000 people (2% of the previous placard holders)
applied for the special placards that allow free parking at
meters. Enforcement is easy because an able-bodied driver
who misuses the distinctive severely disabled placard is
conspicuously violating the law. Illinois adopted a similar
two-tier placard reform in 2012 (Illinois General Assembly
Public Act 097-0845, 2013).
Equity in Performance Pricing
While it is clear that performance-parking prices can
improve transportation effi ciency, are they fair? In San
Francisco, 30% of households do not own a car, so they
do not pay anything for parking (U.S. Census Bureau,
2010). How the city spends its parking revenue also affects
the equity implications of charging for parking.11 San
Francisco uses all its parking meter revenue to subsidize
public transit, so if SFpark increases parking revenue,
higher-income drivers who park at the curb will subsidize
lower-income families who rely on public transit. Also,
because buses are often mired in traffi c congested by
drivers who are cruising for underpriced curb parking,
SFpark will further aid bus riders by reducing traffi c
congestion and increasing bus speeds.
Performance pricing is not price discrimination, which
is a strategy of charging different people different prices for
the same thing. All drivers who park on the same block at
the same time pay the same price. Performance pricing is
also not the same as maximizing revenue. Table 3 shows
that the average price of parking fell by 1% during the fi rst
year of SFpark. Because demand was, on average, inelastic
(−0.4), the city could increase revenue by charging higher
prices. SFpark’s goal, however, is to optimize occupancy,
not to maximize revenue.
Charging demand-responsive prices for curb parking
has even more obvious implications for fairness in develop-
ing countries. Mexico City, for example, is in the process of
adopting a system like SFpark to solve the problems caused
by underpriced and overcrowded curb parking. The current
system leads many drivers to feel they have no alternative to
parking illegally. Although, perhaps exaggerating the prob-
lem, the Los Angeles Times describes this chaotic parking
situation: “Cars dominate nearly every square inch of
Mexico City’s public space. Drivers double- and triple-park
on the streets, to say nothing of curbs, sidewalks, gardens,
alleys, boulevards and bike paths” (Dickerson, 2004, p. 26).
Policies like SFpark will achieve progress toward fair-
ness in Mexico City and in many other cities worldwide for
two reasons. First, fewer than half of households in Mexico
City own a car, and households with a car have an average
income more than twice that of households without a car.12
Therefore, charging performance prices for curb parking
and spending the revenue to pay for public services (e.g.,
public transport and sidewalk improvements) will help the
majority of poorer households without cars at the expense
of richer households who now park free on the streets and
sidewalks. Performance-parking prices will also reduce
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Pierce and Shoup: An Evaluation of Pricing Parking by Demand 79
traffi c congestion and, thus, improve the lives of all transit
riders, pedestrians, and cyclists.
To defend free parking on streets and sidewalks, car
owners sometimes rhetorically push poor people in front of
them as human shields, claiming that charging for parking
will harm the poor. This is inaccurate. Free curb parking
limits the revenue available to pay for public services, and
poor people cannot replace public services with private
purchases as easily as richer people can. The poorest cannot
afford cars, but they do benefi t from public services, such
as public transport, that parking revenues can fi nance.
Using curb-parking revenue to pay for local public services
is much fairer than keeping curb parking free, losing the
revenue needed to pay for public services, creating chaotic
parking problems on busy streets, and increasing traffi c
congestion caused by drivers who are searching for free
parking. Claiming that performance-parking prices will
harm the poor defends a narrow special interest by feigning
a concern for the broad public interest.
Two Suggested Improvements
Our fi ndings suggest at least two ways to improve
SFpark: 1) refi ne its periods of operation and 2) shift from
reaction to prediction in setting prices.
Refi ne the Time Periods
Most meters stop operating at 6 p.m., so anyone who
arrives at 5 p.m. and pays for one hour can park all night.
Drivers who park during the evening thus have an incen-
tive to arrive during the last hour of meter operation while
a few open spaces are still available. Since SFpark sets the
price to achieve an average target occupancy for the three-
hour period from 3 p.m. to 6 p.m., a price can be too high
at 4 p.m. (and occupancy too low) but too low at 5 p.m.
(and occupancy too high).
Operating the meters in the evening for as long as they
are needed to achieve the optimal occupancy can solve this
problem. Free parking after 6 p.m. is a holdover from the
days when meters had one- or two-hour time limits to
increase turnover during the daytime. Most businesses closed
by 6 p.m., so they did not need parking turnover at night.
Because older meters could not charge different prices at
different hours or have different time limits at different times
of day, free parking in the evening made sense.
Because many businesses are now open in the eve-
nings, and meters can charge variable prices and have
variable time limits (or no time limits), the old rationale
for free parking in the evening no longer applies. Meters in
the Port of San Francisco operate until 11 p.m., and several
other cities operate their parking meters until midnight in
the busiest areas, so SFpark will not break new ground by
extending its meter hours past 6 p.m. The purpose of
metering in the evening is to prevent shortages, not to
create turnover.
If SFpark is a good policy before 6 p.m., it does not
become a bad policy after 6 p.m. Because the occupancy
sensors and parking meters are already in place for the pilot
program, it seems unwise to cease operating at 6 p.m.
simply because the old meters did. If pricing to achieve the
optimal parking occupancy reduces cruising, congestion,
traffi c accidents, energy waste, air pollution, and green-
house gases, San Francisco can incrementally extend meter-
ing to additional hours when it will also provide these same
benefi ts. Table 3 shows that SFpark has not increased
curb-parking prices overall, so the major benefi t is better
management, not higher revenue from the existing meters.
Nevertheless, higher revenue can come from installing
more meters and extending meter hours. In 2013, the city
extended meter operation to include Sundays, so SFpark
increased meter revenue without increasing the average
meter rates.
Taking this process to its logical end, SFpark can
continually refi ne its pricing strategy to fi t the demand on
specifi c blocks at different times of the day across different
days of the week. Matching prices to narrow demand
windows will increase the effi ciency of the program.
Shift from Reaction to Prediction
The wide range of occupancy changes after each price
change shows that many factors other than price affect
parking demand. Therefore, basing the next period’s
parking prices only on the previous period’s occupancy
rates will not reliably achieve target occupancy goals. For
example, SFpark should not increase prices in January
because occupancy rates were high during the Christmas
shopping season. Seasonal adjustments based on occu-
pancy rates in previous years may greatly improve the
program’s performance.
SFpark can also adjust prices for other predictable
factors, such as construction projects that reduce the park-
ing supply or events that increase demand. SFpark already
charges special prices during San Francisco Giants games at
AT&T Park: $7 an hour for spaces closest to the ballpark,
and $5 an hour for spaces farther away. For major public
events, such as San Francisco’s Gay Pride Parade that
attracts over a million revelers to the city streets, SFpark
charges up to $18 an hour for curb parking. The current
policy of charging special prices for special events thus
provides a precedent for setting other prices based on
expected demand. Shifting from reaction to prediction in
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80 Journal of the American Planning Association, Winter 2013, Vol. 79, No. 1
adjusting parking prices may allow SFpark to keep parking
occupancy closer to the target rates. Like hockey players
who skate to where the puck is going, SFpark can price
parking based on future demand, not simply on past
occupancy.
Conclusion: A Promising Pilot
Program
SFpark was established as a pilot program to examine
the feasibility of adjusting prices to achieve availability
targets. SFpark appears to be meeting this goal, and other
cities are watching the results closely. Los Angeles has
already adopted a similar program called LA Express Park
(see http://www.laexpresspark.org/).
As a test of new transportation technology, SFpark is
similar to the trial runs of congestion pricing programs in
London, Singapore, and Stockholm. In comparison to
congestion pricing, however, SFpark has shown that park-
ing pricing is relatively simple and cheap. Cities can adopt
programs like SFpark even if they do not yet have all the
resources and political will to adopt congestion pricing. In
effect, performance-parking prices are a poor man’s conges-
tion pricing, and they may represent a step toward full
congestion pricing.
SFpark shows the value of the U.S. Department of
Transportation’s Value Pricing Pilot Program. With a
federal grant of $18 million (one new parking garage can
cost far more), SFpark has shown an entirely new way to
manage on-street parking.13 Unfamiliarity may explain
some skepticism about performance-parking prices, and
only the experience gained in pilot programs will change
minds. Once drivers see that prices decline as well as in-
crease, they may appreciate the availability of open curb
spaces and learn to use information on prices to optimize
their parking choices for every trip. What seemed unthink-
able in the past may become indispensable in the future.
With performance-parking prices, drivers will fi nd
places to park their cars just as easily as they fi nd places to
buy gasoline. But drivers will also have to think about the
price of parking just as they now think about the prices of
fuel, tires, insurance, registration, repairs, and cars them-
selves. Parking will become a part of the market economy,
and prices will help manage the demand for cars and
driving.
If SFpark succeeds in setting prices to achieve the right
occupancy for curb parking, almost everyone will benefi t.
Other cities can then adopt their own versions of perform-
ance-parking prices. Getting the prices for curb parking
right can do a world of good.
Acknowledgments
We are grateful to Eric Agar, Heather Jones, Jay Primus, Chirag Rabari,
Justin Resnick, Hank Willson, and two anonymous referees for their
excellent editorial advice. We are also grateful to Hyeran Lee for assist-
ance with the graphic art. The University of California Transportation
Center provided fi nancial support for our research.
Notes
1. In Boston, for example, the meters charge $1.25 an hour throughout
the city. Glaeser (2013) explains the problems with this policy.
2. In a preface to the article, the editor wrote about Vickrey’s proposal
that “unfortunately, the complexity of the system proposed is that there
is much room for doubt as to its practicability” (1954, p. 62).
3. The title of Vickrey’s 1992 Presidential Address to the Atlantic
Economic Society was “My Innovative Failures in Economics” (Vickrey,
1993). He noted that demand-determined parking prices were his fi rst
venture into marginal-cost pricing, one of the many ideas for which he
received the Nobel Prize in Economics in 1966.
4. Weitzman (1974) demonstrates why the price and quantity approaches
produce the same outcome.
5. The San Francisco Municipal Transportation Authority (2011)
explains how SFpark was established and how it works in more detail.
6. A few meters operate from 7 a.m. to 6 p.m., meters in Fisherman’s
Wharf operate from 7 a.m. to 7 p.m., and some meters in the Port of
San Francisco operate from 7 a.m. to 11 p.m.
7. Newspapers, radio, and television are other sources of information
that frequently report on SFpark. Some residents of San Francisco seem
obsessed about parking, as suggested by a recently published 168-page
guide to parking in the city (Labua, 2011).
8. We used the midpoint formula to measure the price elasticity of
demand because it provides the same result regardless of the direction of
the price change. See Krugman and Wells (2005), for example, for a
discussion of the midpoint formula for the price elasticity of demand.
9. The generally higher levels of traffi c congestion in the afternoon and
on weekdays may also help to explain the more elastic demand for
parking at those times. If traffi c is more congested, a smaller increase in
the price of parking may tip the decision against driving for less
essential trips.
10. We tried to explore whether these blocks were subject to abnormal
exogenous shocks in this time period, such as special events, building
construction, or street closures. Our search did not turn up any abnor-
malities, but we still cannot rule this out as a possibility.
11. Goodwin (1989, 1997), Small (1992), and King, Manville, and
Shoup (2007) emphasize that the use of the revenue from charges on
cars (either from congestion tolls or parking meters) strongly affects
both the equity and political popularity of the charges.
12. The 2010 Mexican National Institute of Statistics and Geography
census found that 46% of households in Mexico City owned at least
one car. Families in Mexico City who owned at least one car had an
average income of 29,280 pesos (U.S. $2,236) per month; families
who did not own a car had an average income of only 11,560 pesos
(U.S. $883) per month.
13. For example, in 2002, UCLA built a new 1,500-space parking
structure for $47 million (Shoup, 2011).
References
Arnott, R., & Inci, E. (2006). An integrated model of downtown parking
and traffi c congestion. Journal of Urban Economics, 60(3), 418–442.
RJPA_A_787307.indd 80RJPA_A_787307.indd 80 5/6/13 12:10:18 PM5/6/13 12:10:18 PM
Downloaded by [University of California, Los Angeles (UCLA)] at 07:20 09 May 2013
Pierce and Shoup: An Evaluation of Pricing Parking by Demand 81
Cooper, M., & McGinty, J. C. (2012, March 15). A meter so expen-
sive, it creates parking spots. New York Times, p. A1.
Dickerson, M. (2004, December 26). Mexico’s economy is vrooming.
Los Angeles Times, p. 26.
Glaeser, E. (2013, February 7). Boston’s plague of cheap parking. Boston
Globe. Retrieved from http://www.bostonglobe.com/opinion/2013/02/
07/boston-plague-cheap-parking/XxeQ6jvF6D0yuEX0HIquaK/story.
html
Goodwin, P. (1989). The rule of three: A possible solution to the
political problem of competing objectives for road pricing. Traffi c
Engineering and Control, 30(10), 495–497.
Goodwin, P. (1997). Inaugural lecture for the professorship of transport
policy. University College London. Retrieved from http://www.cts.ucl.ac.
uk/tsu/pbginau.htm
Goodwin, P. (2001). Traffi c reduction. In K. Button & D. Hensher
(Eds.), Handbook of transport systems and traffi c control (pp. 21–32).
Amsterdam, The Netherlands: Pergamon.
Illinois General Assembly. Public Act 097-0845. Amendment to
Illinois Vehicle Code (January 1, 2013). Retrieved from http://www.ilga.
gov/legislation/publicacts/97/PDF/097–0845.pdf
Kalyanaram, G., & Winer, R. (1995). Empirical generalizations from
reference price research. Marketing Science, 14(3), G161–G169.
King, D., Manville, M., & Shoup, D. (2007). The political calculus of
congestion pricing. Transport Policy, 14(2), 111–123.
Klein, D., Moore, A., & Reja, B. (1997). Curb rights: A foundation
for free enterprise in transit. Washington, DC: The Brookings
Institute.
Krugman, P., & Wells, R. (2005). Microeconomics. New York, NY:
Worth.
Labua, D. (2011). Finding the sweet spot, the insiders guide to parking in
San Francisco. Sausalito, CA: Terrapin Books.
Markoff, J. (2012, June 11). Incentives for drivers who avoid traffi c
jams. New York Times, p. D1.
Mexican National Institute of Statistics and Geography. (2010).
Census of population and housing. Retrieved from http://www.inegi.org.
mx/default.aspx
Michigan Secretary of State. (2001). Disability parking. Retrieved from
http://www.michigan.gov/documents/disability_brochure_33616_7.pdf
Ottosson, D., Chen, C., Wang, T., & Lin, H. (2013). The sensitivity of
on-street parking demand in response to price changes: A case study in
Seattle, WA. Transport Policy 25, 222–232.
San Francisco Municipal Transportation Authority. (2011). SFpark:
Putting theory into practice. Retrieved from http://sfpark.org/wp-content/
uploads/2011/09/sfpark_aug2011projsummary_print-2.pdf
Shoup, D. (2011). The high cost of free parking. Chicago, IL: Planners Press.
Small, K. (1992). Using the revenues from congestion pricing. Trans-
portation, 19(4), 359–381.
Thaler, R. (1985). Mental accounting and consumer choice. Marketing
Science, 4(3), 199–214.
Thompson, W. (1968). The city as a distorted price system. Psychology
Today, 2(3), 28–33.
U.S. Census Bureau. (2010). American Community Survey: City of San
Francisco. Retrieved from http://factfi nder2.census.gov/faces/tableservices/
jsf/pages/productview.xhtml?src=bkmk
Vickrey, W. (1954, November). The economizing of curb parking
space. Traffi c Engineering, 62–67.
Vickrey, W. (1993). My innovative failures in economics. Atlantic
Economic Journal, 21(1), 1–9.
Vickrey, W. (1994). Statement to the Joint Comittee on Washington,
DC, Metropolitan Problems. Journal of Urban Economics, 36, 42–65.
Weitzman, M. (1974). Prices versus quantities. Review of Economic
Studies, 41(4), 477–491.
Wiederholt, M. (2010). Rational inattention. In S. N. Durlauf & L. E.
Blume, The new Palgrave dictionary of economics (online ed.). Retrieved
from http://www.dictionaryofeconomics.com/article?id=pde2010_
R000281
RJPA_A_787307.indd 81RJPA_A_787307.indd 81 5/6/13 12:10:18 PM5/6/13 12:10:18 PM
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