Investigating Land Use Regulation and Transportation Policy with the

San Diego PECAS ModelDimantha I De Silva HBA Specto Incorporated

Daniel Flyte San Diego Association of GovernmentsMathew Keating

John Douglas Hunt HBA / University of Calgary

John E Abraham HBA Specto Incorporated

P roduction

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C onsumption

A llocation

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commoditiesac

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Household activities• Produce labour• Consume goods, services, residential

space

Business, government,

and not for profit activities• Produce goods or services (usually one

type)• Consume goods, services, labour and

nonresidential space

PECAS

1: Where to locate

2: What to make and what to consume in the process (called the ‘technology’ to use)

3: Where to buy what is consumed and where to sell what is made

4: What type of space (floorspace, buildings) to build

5: How much space to build

Just 5 Choices

The interactions among these

Location Choice

Technology Choice

Buying and SellingExchange Choice

location alternatives; buildingwith local and neighbourhood attributes

technology options; vectors of the make and use of items, production processes for establishments and lifestyles for households

exchange locations; where the seller stops and the buyer starts paying for transport

PECAS AA Choice Model(Additive logit model)

Space Development:Simulation of Transitions

parcel-by-parcel microsimulation

Space Development:Simulation of Transitions

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parcel-by-parcel microsimulation

Space Development:Simulation of Transitions

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zoning dictates set of alternatives

parcel-by-parcel microsimulation

Space Development:Simulation of Transitions

Nested logit structure

No changeDemolish DerelictAdd spaceNew space type

QuantityQuantitymulti-level nested discrete-continuous logit

Treatment of Space (Land Areas and Locations)

Treatment of Spaceparcel or grid cell site

Treatment of Space

transport analysis zone (TAZ)

Treatment of Space

land use zone (LUZ)

SANDAG PECAS

SANDAG PECAS ModelApplication: Background• San Diego Association of Governments• Built and calibrated the model

– Iterative approach, starting in 2007– Production-ready and development work streams last

few years, completed 2012• Sensitivity tests and policy analysis• Now using in formal forecasting process

# I TM 2 0 1 4

SANDAG PECAS ModelApplication: Model Design• Standard PECAS Framework

– 46 Activity Types, ~ 9 Household Categories– 85 Commodity Categories, ~ 7 Labor and 35 Space

Types– 236 Land Use Zones– 2005 to 2012 for calibration; 2012 to 2050 for

forecasting– 4-Step Transport Model every 3 years starting 2005

• Rent Smoothing, Construction Control

# I TM 2 0 1 4

PECAS SANDAG Original Motivations• Focus on redevelopment potential

– Not enough capacity though new development– Force thoughtful consideration of different redevelopment

possibilities• Add economic performance analysis to existing forecasting

– Consumer benefit measures– Travel costs are not a good measure of transportation system

performance• Represent economic interactions

– Greater insight into why location and technology/lifestyle choices are made

# I TM 2 0 1 4

Zoning and capacity

Zoning• Permissions that constrain

SD• Developed through review

of published regulations• SANDAG interns guided by

demographers/modelers, ~2009

• Allowed uses• Allowed intensities (FAR)• Each local government

Capacity• Parcel-by-parcel review by

SANDAG and local planners• Envisioned full build-out

development on each parcel• “Planned” development type,

and count of residential units• Reflects historical agreement

as to regional vision

Zoning and capacity

• Initial model runs showed developer profit potential of being allowed to build legally allowed projects at legally allowed intensities.

• Initial purpose of the model• Felt to be too radical, official planning process

(at least for RTP) needed to reflect trends and past agreements

• “Capacity” added to model, for forecasting purposes.

Sensitivity Tests Scenarios• s21: Reference• s22: HH LUZ Capacities Removed• s23: HH LUZ Capacities Removed; Veh Costs x 3• s24: HH LUZ Capacities Removed; Dev Fees = 0• s25: HH LUZ Capacities Removed; Transit Freq x 3

PECAS SANDAG Application: Background

Results

Shifts in Daily Total VMT and VHT

(S21)

(S22)

(S23)

(S24)

(S25)

Removing Household Capacities150kplus 3+ households

Removing Household CapacitiesUnder25k 3+ households

Vehicle Costs X3150kplus 3+ households

Implications

• Forecasting system– But beware: are you ready to let go of your

previous forecasts? • And, are you retiring or changing jobs soon?

– If not, consider constraint or capacity system• Negotiated build-out scenario may not be very

economically efficient– Zoning may be more permissive than you think– Or less permissive than it seems

Implications

• All our travel infrastructure and service plans may be having marginal effects on regional livability (consumer surplus), when compared to strong land use planning visions

• Behavioral spatial economic modeling may indeed force thoughtful consideration of policy– Success! (by original definition…)

• RTP forecasting is different than policy analysis and consensus forecasting– Can contain limited elements of each– But strict timeline and process requirements