Uncertainty in socioeconomic forecasts Todd Graham todd grahammetc

Uncertainty in socioeconomic forecasts Todd Graham <todd. graham@metc. state. mn. us> Metropolitan Council Research

Why forecast? n Provides a reasonable basis for planning ¨ local comprehensive planning ¨ regional system planning Engages stakeholders in addressing growth issues n Helps us understand trends and forces n Forces us to articulate our expectations n 9/11/2021 2

Forecast certainty is not possible DF = Development Framework SD = State Demographer 9/11/2021 3

Many futures are possible n Many scenarios are possible ¨ What do we imagine is the end-state? ¨ What path takes us there? n Starting assumptions that will constrain the range of possibilities ¨ Narrowing 9/11/2021 from the possible to the probable 4

Where does forecasting come in? n Forecast modeling is a system analysis ¨ To represent a set of variables over time ¨ And to represent the dynamics and relationships that move those variables Probable range of futures n Or the most probable future… n ¨ Given a basket of system dynamics, trends, policies, other assumptions 9/11/2021 5

Are multiple forecasts possible? Probable range of futures n Or the most probable future… n ¨ Given a basket of system dynamics, trends, policies, other assumptions 9/11/2021 6

Twin Cities Population Possibilities Range All High Thousands Hi Fert. Hi Migr. Hi Life Exp. Lo Life Exp. All Mid Lo Fert. Lo Migr. All Low 9/11/2021 7

The most probable future(s)? n System dynamics and trends ¨ Can be tweaked as appropriate by forecaster ¨ Or trends can be endogenously modeled, or loaded in from other related models n Policies are variable ¨ Different scenarios to explore policy options ¨ Policymakers decide; forecasters assist ¨ Result is a policy-based forecast – the desired future 9/11/2021 8

Challenges and opportunities Improvement of modeling practices n Integration or coordination of parallel forecast efforts n Engagement of policymakers, planners and publics n 9/11/2021 9

The Future of Forecasts at Met Council Todd Graham <todd. graham@metc. state. mn. us> Metropolitan Council Research

Metropolitan Council’s current model REGIONAL • Jobs • Households • Population LOCAL Land use, current and planned ? ? ? trip generation accessibility • Current model does not consider spatial interactions • Currently, no feedback between land use and transportation dynamics Transportation System Demand distribution Mode choice Network assignment 9/11/2021 11

Complex Metro & Urban Dynamics: Elements and Interactions REGIONAL • Jobs • Population • Households LOCAL Spatial interaction trip generation Acknowledgment: Modified from JD Hunt, et al. (2005) 9/11/2021 production & consumption development & occupancy REGIONAL Economy and labor market dynamics ______ LOCAL price signals accessibility Land floorspace Social & environmental outcomes Transportation System Demand distribution Mode choice Network assignment 12

Expected forecast models workflow n A regional economic model for economic activity, employment, and population ¨ Preferred n A demographic model for parsing population into households ¨ Preferred n model: Pro. Famy (Pro. Famy. com) A land use model for allocating future land use, households and employment to the local level ¨ Preferred n model: Regional Dynamics (Re. Dyn. com) model: Citilabs Cube Land Travel demand model ¨ Currently 9/11/2021 in use: Citilabs Cube Voyager 13

Program Objectives n n n Land economics and geographic science validity Platform for the prediction of likely distributions of development and activity – given a set of rules, or given a set of represented behaviors or dynamics Coordination/integration with Travel Demand Modeling (TDM) and ES capital planning ¨ Model land use dynamics and transport network together – to better represent trends 9/11/2021 14

Goals developed via Needs Assessment Workshops n n n 9/11/2021 A model that balances the need for transparency with the need for realism Able to test a range of policy scenarios A model that provides information on the interaction of the physical environment and development dynamics interact Geographic scope and level of detail necessary for regional systems planning Flexibility to forecast short-term, longterm, and “build-out” 15

2010 9/11/2021 Cube Land 16

Market-based integrated models evaluated against Met Council Needs Assessment Theoretical foundations: n Understandable methodology, with explanation n Traceability of results and ability to perform sensitivity tests Yes n Basis in valid regional and urban development theory Yes Capacity to model and test a wide range of policies Demographic capabilities of model Mostly Yes No – modeled separately Spatial interaction of physical environment and development: n Flexibility to incorporate variety of layers into model Yes n Allocate growth based on transportation network and accessibility measures Yes n Socioec-land use model outputs used as travel demand model inputs Yes Temporal resolution: Ability to forecast 30 years, at 5 -10 -year intervals n Forecast for very-long-term: 50 years Geographic granularity: Micro-level simulation results (parcel level) 9/11/2021 Yes TBD Varies by model 17

Evaluated against Hunt, Kriger, Miller (2005) review of best practices Theoretical foundations: n Real estate market modeled with endogenous pricing – i. e. demand, supply, prices are interdependent and can adjust Yes n Model accounts for key subsystems of region – networks, land use, built environment, activities, travel Yes Capacity to model and test a wide range of policies: Provides Yes measures of benefits and costs of policy alternatives Spatial interaction of physical environment and development: n Framework for modeling interaction between land use and transportation Yes n Transit representation and sensitivity TBD Outputs include predicted land use by type, built environment, segment detail on households and employment industry sectors n Geographic granularity: Analytical units at finest-possible level of detail - Yes Varies by model so as to maximize behavioral simulation Feasibility: Parsimonious data requirements n Manageable implementation requirements (given timeline and budget) 9/11/2021 Cube. Land – Yes 18

Cube Land – a market based model n Equilibrium represented by simultaneous solution of three inter-dependent problems: ¨ Location of real estate consumers ¨ Supply of real estate ¨ Rents and values at marketclearing equilibrium 9/11/2021 19

Background on Martinez’s Modelo de Uso de Suelo de Santiago Martinez, Franisco; and Pedro Donoso. “MUSSA 2: A Land Use Equilibrium Model Based on Constrained Idiosyncratic Behavior of Agents in an Auction Market. ” Paper at TRB Annual Meeting, January 2007. 16 pages. “MUSSA – Land Use Equilibrium Model. ” February 2009 presentation at http: //transp-or 2. epfl. ch/ presentations. Seminaires/MUSSA_Martinez 09. pdf “MUSSA – Its Basis. ” 4 pages. Website at www. mussa. cl/E_fundamentos. html 9/11/2021 20

Cube Land – a market based model n n On demand side, households (h) buy or rent real estate type (v) at certain locations (i) Neighborhood choice (location i) determined by income and willingness to pay: ¨ Bhvi = Ih – {f(Uh–zvi)} n n n Where Uh is typical housing utility for an “h” household Where zvi represents package of amenities, neighborhood characteristics Better package greater willingness to pay ¨ Max n 9/11/2021 (Bhvi – rvi) Subject to available budget of “h” household 21

Cube Land – a market based model n On supply side, developers (j) will offer housing & built space in quantities (S) of certain type (v) at certain locations (i) in order to maximize profit ¨ Max {Svi. J* (rvi – cvi. J)} n n n Subject to regulations at location “i” And all households in region are matched with housing Predicted location choices and predicted supply are calculated with MNL equations (i. e. choice probabilities) 9/11/2021 22

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Integrated modeling n Travel times, accessibility and networks are updated and inform socioeconomic/land modeling at each 5 year step 9/11/2021 Base SE-LU Base Transport Model SE-LU 2010 Updated Network & Access 2010 -15 SE-LU 2015 Updated Network & Access 2015 -20 SE-LU 20## Updated Transport Model 24

Policy and regulation constraints Permissible land uses n Housing unit density min/max n Building height max or FAR max n Protected land planned parks/reserves n GIS coverage of aquifer depletion n Wastewater system capacity constraints? n 9/11/2021 25

Cube Land – a market based model n Equilibrium represented by simultaneous solution of three inter-dependent problems: ¨ Location of real estate consumers ¨ Supply of real estate ¨ Rents and values at marketclearing equilibrium 9/11/2021 26

Cube Land – a market based model n Cube Land outputs not only what land will be developed – but also what types of housing – and prices for real estate zones 9/11/2021 27

Integrated modeling preferred Are these applications possible? … With these tools… Land use/transportation interactions: Assess interactive effects Travel Model Alone? Integrated Modeling Program? No Yes Poorly Yes No Yes of transportation system on land uses, and vice-versa – either “constrained” by land use plans or “free-market” Land Use Analysis: Predict amount and locations of land uses (residential, commercial, industrial, and employment) Smart Growth: Analyze the effects and benefits of Smart Growth strategies (infill and TOD in coordination with transit service) Jobs/Housing Balance: Based on incomes of residents and employees in relation to housing prices Planning strategies: Assess traffic-related effects/benefits of urban growth boundaries, growth management strategies, impact fees Transportation System Management: Effects of land uses and help set priorities among competing projects. A consistent approach for comparing potential improvements or alternatives. 9/11/2021 Source: Johnston, R; and M Mc. Coy. (2006): Assessment of Integrated Transportation-Land Use Models: Final Report. Online at www. ice. ucdavis. edu/um/ 28

Complex Metro & Urban Dynamics: Elements and Interactions REGIONAL • Jobs • Population • Households LOCAL Spatial interaction trip generation Acknowledgment: Modified from JD Hunt, et al. (2005) 9/11/2021 production & consumption development & occupancy REGIONAL Economy and labor market dynamics ______ LOCAL price signals accessibility Land floorspace Social & environmental outcomes Transportation System Demand distribution Mode choice Network assignment 29

Challenges and questions n n n Are the forecasts responsive to economics, market conditions, and urban dynamics? Are the forecasts responsive to – or realistic considering – policies and plans? If so, how? Are the transportation forecasts responsive to future land use and socioeconomics? And vice verse? 9/11/2021 30

Integrated modeling n Travel times, accessibility and networks are updated and inform socioeconomic/land modeling at each 5 year step 9/11/2021 Base SE-LU Base Transport Model SE-LU 2010 Updated Network & Access 2010 -15 SE-LU 2015 Updated Network & Access 2015 -20 SE-LU 20## Updated Transport Model 31

Integrated Models - Paths of Advancement Land Use Model Travel Demand Model Land Capacity, Trends, Judgment No Transit No Mode Split Transit Logit Model Split Advanced Aggregate Activity-based Met Council in 2008 Non-market-based land allocation Land allocation with price signals Fully integrated market-based model Path of advancement Met Council in 2010 Ideal Model Source: Miller, EJ, et al (1999): Integrated Urban Models for Simulation of Transit and Land Use Policies. http: //onlinepubs. trb. org/Onlinepubs/tcrp_rpt_48. pdf

Integrated modeling as a policy ideal n Transportation Policy: SAFETEA-LU and ISTEA ¨ Coordination of land use and transportation planning n NEPA and Clean Air Act ¨ Land development patterns must be consistent with regional transportation plan 9/11/2021 33

Uncertainty in socioeconomic forecasts Todd Graham <todd. graham@metc. state. mn. us> Metropolitan Council Research