Question Purpose: Where is local parking supply greater than demand, and where is local demand greater than supply, and at what prices for parking does this hold? Does this vary systematically by type of place or other criteria?

This is a fundamental question that addresses the relationship between parking supply, demand, and pricing. This question is to provide guidance for MTC, ABAG, cities, and transit agencies to assess the potential for local parking pricing policies to be applied to the Bay Area. The conditions that led to those policies will be assessed for application to other cities and be used to support the program and assess the potential applicability and/or success for various parking pricing policies. Local jurisdictions are primarily interested in the answers to these questions within their own jurisdictions. These questions are especially dependent on parking economics. Each specific location will have its own balance of supply, demand, and price elasticity that will determine how a set price affects the relationship between supply and demand. Factors affect supply and demand are location-dependent—including demographics, transportation options in the area, local and regional policies, as well as culture. The figure below illustrates the relationships between parking demand, supply and price.

Source: Concept and information from Richard Willson; adapted and edited by CDM Smith, February 2014.

Data analysis methods for this question can be used by local jurisdictions for development of specific strategies. Supply and occupancy data can establish a baseline for comparative analysis, allowing local jurisdictions to evaluate how the relationship between parking supply, demand, and price in their jurisdiction compares to the larger region. Variations in data will be grouped by type of place, demographic, and land use criteria to help organize data so that analysis findings can be compared to areas of similar environments.

Literature Review

Parking Supply, Demand and Pricing

“Underpriced and overcrowded curb parking creates problems for everyone except a few lucky drivers who find a cheap space,” Donald Shoup explains in the introduction to his research on demand based pricing in San Francisco (2013). However, while underpricing and overcrowding creates problems, overpricing and under-crowded spaces have other negative effects.

Professor Donald Shoup, an expert on parking economics, suggests keeping prices consistent with an occupancy level of approximately 85% in order to realize the “right price” for parking. For areas with more supply than demand, unused parking spaces could be converted to more efficient land uses (such as developments, public space, or parklets); excess (underutilized) parking in these areas could also be used by adjacent high-demand areas through via shared parking policies or valet parking policies (see Policy Question #7-11 for application descriptions). Additional literature relating supply, demand, and pricing includes:

• SFPark, goBerkeley, and New York City’s Variable Pricing Pilot projects: each of these projects, explained in detail below, include cutting-edge research on managing on-street parking with variable pricing.
• Transpo Group (2013). Seattle Annual Paid Parking Occupancy Report 2013. Prepared for the Seattle Department of Transportation: This study looks at parking conditions where parking pricing is in effect. Occupancy varies by time of day for different locations with different prices and enforcement policies in place.
• Auchincloss et al. (2014). Public Parking Fees and Fines: A Survey of U.S. Cities. (PDF) Published in Public Works Management & Policy: This study looks at parking prices within 107 U.S. cities and finds that higher parking costs are associated with an increase in public transit use and less personal automobile demand.
• Some studies have also looked at the relationship between supply and demand, including Robert Cervero’s (2009) study in California that found an 11% decrease in parking demand for every 50% reduction in supply (PDF).
• Brian Canepa and Joshua Karlin-Resnick’s article Releasing the Parking Brake on Economic Development (May 2015) from Planning Magazine offers three example cities who have lowered or abolished mandatory parking minimums and the success they are having drawing in development to their downtown.

Price Elasticity of Demand

Several studies have studied how parking prices change demand, calculating price elasticity of demand for different regions. The change in demand due to changes in price is also dependent on supply. Because of this, these effects are very location-specific. These studies show a range of price elasticities, from -0.15 to -0.58. These include:

• Kelly and Clinch (2009): A study in Dublin, Ireland found an average price elasticity of demand of -0.29. PDF
• Dueker, et al (1998): A study in Portland found a 5.8% decrease in demand per 10% increase in price using an $80/month base charge (elasticity of -0.58). PDF
• Shoup (1994): Study found a 1.5% decrease in demand per 10% increase in price (elasticity of -0.15).
• Pierce and Shoup (2013): An SFPark study found an average price elasticity of demand of -0.40. Additionally, Millard-Ball, Weinberger, and Hampshire (2014) [PDF] look at the impacts of SFPark’s pricing research, detailed further within the discussion for Policy Question #7.

Parking and Affordable Housing

The Bay Area Council Poll in 2014 found that 79% of those polled (in all nine counties) said that the Bay Area faces “crisis in housing costs.”Inclusion of parking increases the cost of building housing, limiting the amount of housing that can be produced under a set budget. Demand for more affordable housing in the Bay Area is sky-high, resulting in long waiting lists. The following studies specifically look at how minimum requirements affect affordable housing:

• The study, Parking Utilization in Affordable Housing in San Diego, CA (Willson, O’Connor, and Hajjiri, 2012) looks at housing affordability and parking demand and finds that demand for parking is lower than the built supply and assessing the policies that will cause individuals to determine whether vehicle ownership is worth the cost. The study found that demand for parking in affordable housing rental units was approximately half that of market rate rental units in San Diego. Furthermore, there was a direct relationship between parking demand and income level. In several affordable and senior housing developments in San Diego, data collection showed that utilization rates were only a small proportion of the minimum requirements under code.
• Due to lower car ownership rates within low-income groups, parking in affordable housing developments often go unused, yet the requirements still increase the rental costs. “Parking Requirement Impacts on Housing Affordability,” (Litman, 2013) estimates that a single parking space increases the price of a housing unit by 12.5%. Demand can be influenced by household income, tenure, household size, population density and alternative transportation, as well as pricing policies. Despite lower demand in many areas with more transit options and lower-income populations, parking requirements are typically set at the same rate for all housing.

Best Practice Research

Variable Pricing

Policy Application: New York City’s Variable Pricing Pilot

New York City received an FHWA grant to implement demand-based variable pricing. The conditions that led to the program’s initiation were a high rate of cruising for parking, low availability of parking during peak demand periods, and a high rate of double parking. Within Greenwich Village, pricing was raised from $1 to $2 during the peak demand period from noon to 4pm. Occupancy on weekdays decreased about 8% on weekdays and vehicle turnover increased, allowing a higher number of total vehicles to park. Results of the 6-month pilot were well documented and success of the program resulted in continuing the variable pricing policy, raising the fees to $2/hour off-peak and $3/hour during peak periods.

Policy Application: Berkeley’s goBerkeley Pilot

In 2013, with funding from the Federal Highway Administration (FHWA), the City of Berkeley initiated a pilot program that implemented several on-street dynamic pricing strategies. Hourly rates for on-street parking range from $1.00 to $2.25; prices were set based on the demand for parking in the area. In the Elmwood District, a popular commercial corridor with limited on-street parking, a tiered-parking strategy was implemented to encourage short-term parking and discourage longer-term parking. Prices start at $1.00 and increase $0.50 for every additional hour of stay, up to three hours. Pilots were also initiated in the Downtown Berkeley and Southside/Telegraph neighborhoods. In these areas premium and value areas were established. The higher demand premium areas had shorter time limits and higher hourly rates to encourage turnover, and lower demand value areas had longer time limits and lower hourly rates.

Off-street lots are commonly priced higher than on-street parking, resulting in underutilized off street parking and excess demand (double parking) within on-street parking in high demand areas. Off-street parking typically needs to be less expensive to encourage longer term parking, increasing availability of on-street parking for short-term parking. In 2013, Berkeley found that the $0.50/hour higher cost for on-street parking (at $1.50/hour) compared to off-street costs (at $1.00/hour) was not sufficient to encourage parkers to use off-street facilities over on-street facilities. Even with this price differential, on-street parking was still consistently above 85% occupied while off-street facilities were before 75% occupied. This study resulted in recommendations that the pilot implement addition pricing measures to make off-street parking more competitive with on-street parking.

Policy Application: SFpark’s Demand-Based Pricing

With funding from the FHWA in 2011, San Francisco began an ambitious program to set on-street parking prices at variable levels dependent on the demand for that area. Seven pilot zones were selected to have demand-based pricing, with prices adjusted every few weeks based on occupancy rates. For example, if occupancy rates are below 30%, the price is decreased by 50 cents per hour; if occupancy is above 80%, the price is increased 25 cents per hour (Figure: Weekday Morning Prices at Fisherman’s Wharf).

There are several benefits of the SFpark program. First, vehicles spend less time circling for parking. This reduces traffic congestion and decreases emissions from excess driving. Second, drivers parked in the areas of higher demand will typically park for a shorter time, increasing turnover rate and therefore, making these spaces available to accommodate more people. Last, more people may use alternative modes and carpool to highly demanded destinations with the highest prices, such as baseball games at AT&T Park.

Pierce and Shoup (2013) calculated the price elasticity of demand based on SFPark data of 5,294 changes in price and occupancy within San Francisco. Overall, over the course of the study, meter prices did not increase overall—meters were adjusted both up and down with the average meter price falling 1%. The average elasticity value calculated was -0.4. Therefore, as the cost for parking increased by $1, occupancy fell by 40%. In other words, on a street block-face with 10 spaces, raising the price by 25 cents will open up one parking space.

After the program had been in effect for six months, Pierce and Shoup (2013) looked at two of the seven pilot areas to calculate the price elasticity of demand based on SFPark’s data showing price and occupancy changes in 2012. The study found that the price elasticity of demand in an area at Fisherman’s wharf was -1.3. Here, demand for parking was low (average occupancy at 27%) and prices were decreased to reach higher occupancies. For every $1 decrease in price per hour, occupancy increased 130% (Table: Price and Demand Changes for Two SFPark Study Areas). Even though per hour prices decreased, the parking revenue for the Beach Street area increased, because occupancy increased substantially.

Area	Change in Price	Change in Occupancy	Price Elasticity of Demand
600 block area near Beach Street at Fisherman’s Wharf	-53%$3/hr to $1.75/hr	+70%27% to 56% occupied	-1.3
200 block area at and near Drumm Street	+25%$3.50/hr to $4.50/hr	-13%98% to 86% occupied	-0.5

Local Best Practice: MTC 2012 Smart Parking Workshop Survey

Policy changes require support from City staff, developers, advocates, and/or private citizens in order to initiate change. The conditions that lead to successful parking policies are not wholly based on the physical parking conditions, but largely based on political openness and readiness. In June 2012, MTC held a workshop on parking reform. A survey of local representatives (with a range of stakeholders, local representatives and citizens) after the workshop showed that 65% of respondents are likely to support parking reform in their cities. Over 50% of respondents stated that their Cities are considering and/or pursuing shared parking and employee programs.

Local Best Practice: Local Parking Pricing Policy Interest

In 2011, a survey administered by MTC asked cities if different parking policy actions were: currently implemented, short term interest, long term interest, or no interest. Many cities—including Sonoma, Martinez, Alameda, Mountain View, Emeryville, Hayward, and South San Francisco—stated parking pricing as a short term interest despite no current pricing policies. Other cities stated other indirect parking pricing policies in their short term interests. The town of Windsor, Campbell, and San Carlos, for example, stated reduced parking requirements in their short term interests.