Transcript Economic component - Water and Watersheds

Role of Economics in W&W Project
and in Climate Change Projects
 Explain how land use patterns evolve
over time
 Forecast future land use change
 Determine how different policies might
produce different future land use
patterns
How Do Different Approaches to Modeling
Land Use Change Compare?
 Build-Out Analysis:
 Accepts Transportation Analysis Zone
Small Area Population Forecasts
 Spreads Forecasted Population Change
Over Space According to Zoned Densities
 Geostatistical Simulation (cellular automata)
 Landscape is Divided into Cells
 Transition Rules are Functions of State and
Location of Cell and State of Neighbor
 Economic Modeling
 Model is “process-based”, “mechanistic”,
“behavioral”
 Parcel Owner Chooses Optimal Time and
Density of Development
 Factors Taken Into Account that Affect
Decision are:
•
•
•
•
Value of parcel in undeveloped use
Value of parcel in developed use
Costs of converting parcel to developed use
… and how these are changing over time…
Build-Out Analysis
Geostatistical Simulation
(e.g. Sleuth)
Economic Modeling
Unit of
Observation
Transportation Analysis
Zone
Cell in landscape
Privately owned parcel of land
Nature of
Approach
Accounting procedure
Pattern-based
Process-based
Nature of
land use
change
process
Deterministic process
dictated by regulations
Stochastic process with
transition rules based on:
“slope”, “spread”, “breed”,
“dispersion”, “road gravity”
coefficients
Stochastic model of behavior of
land owners (choosing optimal
timing of development and
optimal density of
development)
“Driving
Forces”
Current maximum
density allowed by
zoning
State of current land cover
Visible features of landscape
(location, physical
characteristics)
Value in undeveloped use,
Value in developed uses, and
Conversion costs,
All as functions of:
Current land cover
Physical, locational features
Public goods provision
Relevant regulations
…
Build-Out
Analysis
Geostatistical Simulation
(e.g. Sleuth)
Economic Modeling
Analytical
Method
GIS overlays
Cellular automata models simulate observed cell changes by
calibrating set of 5 transition rule
coefficients
Discrete choice or hazard model
analysis - tests hypotheses and
produces parameter estimates for
forecasting
Treatment of
interactions
None
Interactions between cell and
neighboring cell important in
“spread” rule
Interactions important if
surrounding land use affects
value of land in particular use
Treatment of
stochastic nature
of problem
None
Forecasts are probabilistic
(probability cell will be
converted)
Forecasts are probabilistic
(probability parcel will be
converted)
Data used
Current zoning in Landsat data for at least 4 points
GIS form
in time;
Road networks for 2 points in
time
Parcel level data including
locations of parcels,
GIS data on physical features,
regulations, public goods, land
cover, …
Source of
growth pressure
information
“Small area”
population
forecasts
Economic model of housing
starts as function of regional
economic variables
None, just matches pattern
Other modeling approaches fail to
account for the fact that…
policies do not dictate outcomes; they provide
incentives/disincentives or constraints on
individuals’ decisions.
If you don’t know how policies affect
individuals’ decisions…
you can’t predict future land use outcomes under
varying policies.
Examples of Growth Control Policies
 “Downzoning” (increasing the min. lot size or
decreasing the maximum allowable density)
 Imposing open space and clustering
requirements
 Restricting the provision of public utilities
 Instituting agricultural preservation programs
 Designating “Priority Funding Areas”
 Enforcing adequate public facilities moratoria
None can be incorporated in current cellular automata models,
but can be incorporated in models of economic decision making.
Tasks for Economics Component in
Current Climate Change Project
 Produce 20-50 year land use change forecasts:
 Using the “build out” analysis approach
 Using the economic modeling approach –
with and without Smart Growth policies
 Devise a means of translating probabilistic
outcomes of models into forecast scenarios
usable by other PI’s:
 Use Monte Carlo simulations to determine
variability of resulting pattern due to inherent
randomness of process.
Tasks for Economics Component in
Proposed Climate Change Project
Determine spatially-explicit scenarios, taking into
account the following dynamic elements:
 growing population and changing demographics;
 changing land use policies;
 receding coastline due to sea level rise;
 adoption of climate change response policies (e.g.
taxes on carbon emissions, subsidies for carbon
sequestration)