Uncertainty in socioeconomic forecasts

Uncertainty in socioeconomic forecasts

Todd Graham Metropolitan Council Research

Why forecast?Provides a reasonable basis for planninglocal comprehensive planningregional system planningEngages stakeholders in addressing growth issuesHelps us understand trends and forcesForces us to articulate our expectations

Forecast certainty is not possibleDF = Development FrameworkSD = State Demographer

Chart2

1.52519601960196019601960

1.8751.87519701.87519701970

1.9862.195221.9861.986

2.2892.562.2612.2222.2042.141

2.6422.8882.4712.3562.312.231

201020102010201020102.275

Census

DF 1975

DF 1978

SD 1975

DF 1986

SD 1983

Population (Millions)

Sheet1

CensusDF 1975SD 1975DF 1978SD 1983DF 1986BP 1994BP 1998SD 1998BP 2002SD 2002DF 2004SD 2007

19601.525

19701.8751.8751.875

19801.9862.195221.9861.986

19902.2892.562.2222.2612.1412.2042.289

20002.6422.8882.3562.4712.2312.312.5792.6092.5722.6422.6422.6422.642

20102.2752.7892.8382.7712.962.9723.0052.907

20202.9773.0912.9063.2823.2253.3343.134

20303.5733.4113.6073.287

Sheet1

Census

DF 1975

DF 1978

SD 1975

DF 1986

SD 1983


Sheet2

Census

DF 2004

BP 1998

DF 1986


Sheet3

Census

SD 2002

SD 2007

SD 1998

SD 1983


Census

DF 2004

SD 2002

SD 2007

BP 1998

SD 1998


Many futures are possibleMany scenarios are possibleWhat do we imagine is the end-state?What path takes us there?Starting assumptions that will constrain the range of possibilitiesNarrowing from the possible to the probable

Where does forecasting come in?Forecast modeling is a system analysisTo represent a set of variables over time And to represent the dynamics and relationships that move those variablesProbable range of futuresOr the most probable futureGiven a basket of system dynamics, trends, policies, other assumptions

Are multiple forecasts possible?Probable range of futures Or the most probable futureGiven a basket of system dynamics, trends, policies, other assumptions

Twin Cities Population Possibilities RangeThousands

The most probable future(s)?System dynamics and trends Can be tweaked as appropriate by forecasterOr trends can be endogenously modeled, or loaded in from other related modelsPolicies are variableDifferent scenarios to explore policy optionsPolicymakers decide; forecasters assistResult is a policy-based forecast the desired future

Challenges and opportunitiesImprovement of modeling practicesIntegration or coordination of parallel forecast effortsEngagement of policymakers, planners and publics

The Future of Forecasts at Met Council


REGIONAL JobsHouseholdsPopulation

Land use, current and plannedMetropolitan Councils current model

LOCAL Current model does not consider spatial interactions Currently, no feedback between land use and transportation dynamics???Transportation SystemDemand distribution Mode choice Network assignmentaccessibilitytrip generation

Complex Metro & Urban Dynamics: Elements and InteractionsSpatialinteractionpricesignalsLand andfloorspaceREGIONALEconomy and labor market dynamics___________LOCALdevelopment & occupancyproduction & consumptionAcknowledgment:Modified from JD Hunt, et al. (2005)REGIONAL JobsPopulationHouseholds

LOCALSocial & environmental outcomesTransportation SystemDemand distribution Mode choice Network assignmentAcknowledgment:Modified from JD Hunt, et al. (2005)accessibilitytrip generation

Expected forecast models workflowA regional economic model for economic activity, employment, and populationPreferred model: Regional Dynamics (ReDyn.com)A demographic model for parsing population into householdsPreferred model: ProFamy (ProFamy.com)A land use model for allocating future land use, households and employment to the local levelPreferred model: Citilabs Cube LandTravel demand modelCurrently in use: Citilabs Cube Voyager

Program ObjectivesLand economics and geographic science validityPlatform for the prediction of likely distributions of development and activity given a set of rules, or given a set of represented behaviors or dynamicsCoordination/integration with Travel Demand Modeling (TDM) and ES capital planningModel land use dynamics and transport network together to better represent trends

Goals developed via Needs Assessment WorkshopsA model that balances the need for transparency with the need for realismAble to test a range of policy scenariosA model that provides information on the interaction of the physical environment and development dynamics interactGeographic scope and level of detail necessary for regional systems planningFlexibility to forecast short-term, long-term, and build-out

Market-based integrated models evaluated against Met Council Needs Assessment

Evaluated against Hunt, Kriger, Miller (2005) review of best practices

Cube Land a market based modelEquilibrium represented by simultaneous solution of three inter-dependent problems:Location of real estate consumersSupply of real estateRents and values at market-clearing equilibrium

Background on Martinezs Modelo de Uso de Suelo de SantiagoMartinez, 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-or2.epfl.ch/ presentationsSeminaires/MUSSA_Martinez09.pdfMUSSA Its Basis. 4 pages. Website at www.mussa.cl/E_fundamentos.html

Cube Land a market based modelOn 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(Uhzvi)}Where Uh is typical housing utility for an h householdWhere zvi represents package of amenities, neighborhood characteristicsBetter package greater willingness to payMax (Bhvi rvi)Subject to available budget of h household

Cube Land a market based modelOn supply side, developers (j) will offer housing & built space in quantities (S) of certain type (v) at certain locations (i) in order to maximize profitMax {SviJ* (rvi cviJ)}Subject to regulations at location iAnd all households in region are matched with housingPredicted location choices and predicted supply are calculated with MNL equations (i.e. choice probabilities)

Integrated modelingTravel times, accessibility and networks are updated and inform socioeconomic/land modeling at each 5-year stepBase TransportModelUpdated Network & Access 2010-15Updated Network & Access 2015-20Updated TransportModelBase SE-LUSE-LU 2010SE-LU 2015SE-LU 20##

Policy and regulation constraintsPermissible land uses Housing unit density min/maxBuilding height max or FAR maxProtected land and planned parks/reservesGIS coverage of aquifer depletionWastewater system capacity constraints?

Cube Land a market based modelEquilibrium represented by simultaneous solution of three inter-dependent problems:Location of real estate consumersSupply of real estateRents and values at market-clearing equilibrium

Cube Land a market based modelCube Land outputs not only what land will be developed but also what types of housing and prices for real estate zones

Integrated modeling preferredSource: Johnston, R; and M McCoy. (2006): Assessment of Integrated Transportation-Land Use Models: Final Report. Online at www.ice.ucdavis.edu/um/

Complex Metro & Urban Dynamics: Elements and InteractionsSpatialinteractionpricesignalsLand andfloorspaceREGIONALEconomy and labor market dynamics___________LOCALdevelopment & occupancyproduction & consumptionAcknowledgment:Modified from JD Hunt, et al. (2005)REGIONAL JobsPopulationHouseholds

LOCALSocial & environmental outcomesTransportation SystemDemand distribution Mode choice Network assignmentAcknowledgment:Modified from JD Hunt, et al. (2005)accessibilitytrip generation

Challenges and questionsAre 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?

Integrated modelingTravel times, accessibility and networks are updated and inform socioeconomic/land modeling at each 5-year stepBase TransportModelUpdated Network & Access 2010-15Updated Network & Access 2015-20Updated TransportModelBase SE-LUSE-LU 2010SE-LU 2015SE-LU 20##

Integrated Models - Paths of AdvancementTravel Demand ModelLandUse ModelNo TransitNo Mode SplitLand Capacity, Trends, JudgmentNon-market-basedland allocationLand allocationwith price signalsFully integrated market-basedmodelPath of advancementTransit Logit Model SplitAdvancedAggregateActivity-basedIdeal ModelMet Council in 2008Met Council in 2010Source: Miller, EJ, et al (1999): Integrated Urban Models for Simulation of Transit and Land Use Policies. http://onlinepubs.trb.org/Onlinepubs/tcrp/tcrp_rpt_48.pdf

Integrated modeling as a policy idealTransportation Policy: SAFETEA-LU and ISTEACoordination of land use and transportation planningNEPA and Clean Air ActLand development patterns must be consistent with regional transportation plan

Uncertainty in socioeconomic forecasts


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Uncertainty in socioeconomic forecasts