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Investigating Land Use Regulation and Transportation Policy with the San Diego PECAS Model. P roduction E xchange C onsumption A llocation S ystem. Goods, Services, Labour and Space. $. $. $. $. $. $. $. Producing Sectors. $. $. $. $. $. $. $. $. $. Economic Flows. $. $.
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Investigating Land Use Regulation and Transportation Policy with the San Diego PECAS Model
Production Exchange Consumption Allocation System
Goods, Services, Labour and Space $ $ $ $ $ $ $ Producing Sectors $ $ $ $ $ $ $ $ $ Economic Flows $ $ $ $ $ $ Consuming Sectors $ $ $ $ $ $ $ $ $ $ $ $ $
Goods, Services, Labour and Space commodities $ $ $ $ $ $ $ Producing Sectors $ $ $ $ $ $ $ $ $ activities Economic Flows $ $ $ $ $ $ Consuming Sectors $ $ $ $ $ $ $ $ $ $ $ $ $
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
Just 5 Choices 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 The interactions among these
PECAS AA Choice Model (Additive logit model) Location Choice location alternatives; building with local and neighbourhood attributes Technology Choice technology options; vectors of the make and use of items, production processes for establishments and lifestyles for households Buying and Selling Exchange Choice exchange locations; where the seller stops and the buyer starts paying for transport
Space Development: Simulation of Transitions
Space Development: Simulation of Transitions parcel-by-parcel microsimulation
no change more the same mid density residential commercial industrial derelict quantity Space Development: Simulation of Transitions parcel-by-parcel microsimulation
no change more the same mid density residential commercial industrial derelict quantity Space Development: Simulation of Transitions parcel-by-parcel microsimulation zoning dictates set of alternatives
Nested logit structure New space type Add space No change Demolish Derelict multi-level nested discrete-continuous logit Quantity Quantity
Treatment of Space parcel or grid cell site
Treatment of Space transport analysis zone (TAZ)
Treatment of Space land use zone (LUZ)
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 #ITM2014
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 #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 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 • 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
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.
PECAS SANDAG Application: Background 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
(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