Investigating Land Use Regulation and Transportation Policy with the San Diego PECAS Model Dimantha I De SilvaHBA Specto Incorporated Daniel Flyte San Diego Association of Governments Mathew Keating John Douglas HuntHBA / University of Calgary John E AbrahamHBA Specto Incorporated

P roduction E xchange C onsumption A llocation S ystem

$ $$ $ $ $ $ $$ $ $ $ $ $ $$ $ $ $ Producing Sectors Goods, Services, Labour and Space Consuming Sectors $ $ $$ $ $ $ $ $ $ $ $ $ $ $ $ Economic Flows

$ $$ $ $ $ $ $$ $ $ $ $ $ $$ $ $ $ Producing Sectors Goods, Services, Labour and Space Consuming Sectors $ $ $$ $ $ $ $ $ $ $ $ $ $ $ $ Economic Flows commodities activities

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 Selling Exchange Choice location alternatives; building with 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

more the sameno changemid density residentialcommercialindustrial derelict quantity parcel-by-parcel microsimulation Space Development: Simulation of Transitions

more the sameno changemid density residentialcommercialindustrial derelict quantity zoning dictates set of alternatives parcel-by-parcel microsimulation Space Development: Simulation of Transitions

Nested logit structure No changeDemolishDerelictAdd spaceNew space type Quantity multi-level nested discrete-continuous logit

Treatment of Space (Land Areas and Locations)

Treatment of Space parcel or grid cell site

Treatment of Space transport analysis zone (TAZ)

Treatment of Space land use zone (LUZ)

SANDAG PECAS

SANDAG PECAS Model Application: 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 #ITM2014

SANDAG PECAS Model Application: 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 #ITM2014

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 #ITM2014

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 Capacities 150kplus 3+ households

Removing Household Capacities Under25k 3+ households

Vehicle Costs X3 150kplus 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