Economic Modeling for
Water Resources
John B. Braden
University of Illinois
at Urbana-Champaign
NSF Interdisciplinary Modeling Workshop – July 2005
Thanks:
Laurel Saito
 Heather Segale
 Xiaolin Ren

NSF Interdisciplinary Modeling Workshop – July 2005
Contributions of Economics

Understand Behaviors
– Responses to institutions & policies
– Market power (size, information)
– “Positive” analysis

Design Institutions & Policies
– Benefit/cost analysis
– Planning for behaviors
– “Normative” analysis
NSF Interdisciplinary Modeling Workshop – July 2005
Limitations of Economics
Anthropocentric
 Utilitarian
 Statistical
 Allocational (efficiency)
 Material

NSF Interdisciplinary Modeling Workshop – July 2005
Economic Modeling

Theory – generate hypotheses

Econometrics – test hypotheses

Operations Research
– simulate outcomes
– optimize complex systems
NSF Interdisciplinary Modeling Workshop – July 2005
Outline of Presentation
1.
2.
3.
4.
5.
6.
7.
Basic Economic Models
Pricing Aquatic Ecosystems
Hydro-Economic Models
Bio-Economic Models
Benefit-cost Analysis
Risk and Uncertainty
Summary Remarks
NSF Interdisciplinary Modeling Workshop – July 2005
Resources for Lecture

Griffin, R.C. Water Resource
Economics. MIT Press (forthcoming)

Young, R.A. Determining the
Economic Value of Water.
Resources for the Future (2005)

Other books & articles on website
NSF Interdisciplinary Modeling Workshop – July 2005
1. Basic Economic Models
NSF Interdisciplinary Modeling Workshop – July 2005
Agent Models

Consumers Maximize Utility
Max u(Y,w) , uy, uw > 0
uyy, uww < 0
s.t. PYY + pww < B

Producers Maximize Profit
Max π = p1y1 – Σi cixi – cww
s.t. y1 = f(X, w) , fx, fw > 0;
fxx, fww < 0
NSF Interdisciplinary Modeling Workshop – July 2005
Marginal Analysis

Marginal benefits = incremental
demand price

Marginal costs = incremental
supply price

Operating returns vs. fixed costs
NSF Interdisciplinary Modeling Workshop – July 2005
Supply Model – Input Choice
X
y12
X
y11
y10
W
W
Slope  
NSF Interdisciplinary Modeling Workshop – July 2005
CW
CX
Supply Model – Output
C
 S1 (C X , CW )
y1
P1
P1
y1
NSF Interdisciplinary Modeling Workshop – July 2005
y1
Aggregate Supply
P1
S1p
S1q
S1Agg
y1
NSF Interdisciplinary Modeling Workshop – July 2005
Demand Model
P1
D
 d1 ( P1 , P, B)
P1
y1
NSF Interdisciplinary Modeling Workshop – July 2005
Aggregate Demand
P1
d1a
d1b
d1Agg
y1
NSF Interdisciplinary Modeling Workshop – July 2005
Nonrival (“Public”) Goods

Rival – Ordinary goods that only one
person can consume

Nonrival – Goods that can be
consumed by many simultaneously
– Excluability allows pricing
NSF Interdisciplinary Modeling Workshop – July 2005
“Public Goods” & Economic Value
Pz
d
a
z
d
b
z
d zAgg
z
NSF Interdisciplinary Modeling Workshop – July 2005
Markets
Producers offer good & buy inputs
 Consumers bid for goods & supply
labor
 Prices coordinate producers &
consumers

– Output markets (py, pw)
– Input markets (ci, cw)
– Parametric to individuals
NSF Interdisciplinary Modeling Workshop – July 2005
Market Model
P1
S1agg
P1M
d1agg
M
1
y
y1
NSF Interdisciplinary Modeling Workshop – July 2005
Welfare Analysis (normative)

Maximize Net Benefits
– “Consumer surplus”
– “Producer surplus” [returns to owners
& fixed inputs]

Competitive Equilibrium  Social
Optimum
NSF Interdisciplinary Modeling Workshop – July 2005
Welfare Analysis – Economic Surplus
PW
SW
Consumer Surplus
PW*
DW
Producer Surplus
W
*
NSF Interdisciplinary Modeling Workshop – July 2005
W
2. Pricing Aquatic Ecosystems
NSF Interdisciplinary Modeling Workshop – July 2005
The Diamond-Water Paradox
Diamond fetch very high prices,
although they have limited
usefulness. Water is essential to
life, but fetches very low prices.
WHY?
NSF Interdisciplinary Modeling Workshop – July 2005
Total vs. Marginal Value -- Water
Value
TVW
SWAgg
PW
MVW
W
NSF Interdisciplinary Modeling Workshop – July 2005
Total vs. Marginal Value -- Gems
Value
SGAgg
TVG
PG
MVG
G
NSF Interdisciplinary Modeling Workshop – July 2005
Answering the Paradox

Water: Adequate supplies produce
low marginal value (even though
basic water needs are highly valued).

Diamonds: Limited supplies produce
high marginal value.
NSF Interdisciplinary Modeling Workshop – July 2005
Pricing Aquatic Ecosystems

Whole vs. components

Value vs. supply cost

Use vs. nonuse
NSF Interdisciplinary Modeling Workshop – July 2005
Models for Valuing Ecosystems

Market-based (Revealed Preferences):
– Expenditures on services – fish & fishing;
whale watching
– Opportunity cost of laws –Lagragian
multipliers on constraint functions
– Replacement cost

Experiment-based (Stated Preferences):
– Trade-offs between service levels & prices
– Willingness to support tax referenda
– Expressed willingness to pay
NSF Interdisciplinary Modeling Workshop – July 2005
Example: Value of ∆ Fishery Quality
Pf
Pf*
D f ( P, Q2 )
D f ( P, Q1 )
f
NSF Interdisciplinary Modeling Workshop – July 2005
Example: Value of Wetlands
(Earnhart, Land Econ., 2001)

Hedonic housing value – price differentials for
homes adjacent to restored wetland vs. not
adjacent to any distinct features
– Proximity to L.I. Sound, river, stream ~ + 3%
– Proximity to restored marsh ~ +16%
– Proximity to disturbed marsh ~ -13%

Conjoint choice – selecting between hyp.
homes differing in amenities & price
– All values ~ 80 – 120%
NSF Interdisciplinary Modeling Workshop – July 2005
Example: “The Value of the World’s
Ecosystem Services & Natural Capital”
(Costanza et al., Nature, 1997)



Benefits transfer – borrow marginal values
from literature and apply them to
increments to env. quality or natural
resources
Multiply by total quantity of natural
resources
Total value ~ $33 trillion
NSF Interdisciplinary Modeling Workshop – July 2005
Example: “The Value …” Critique

“Serious underestimate of infinity.”

Total value vs. marginal value
– Tools best applied to small changes from
status quo

Double - counting
NSF Interdisciplinary Modeling Workshop – July 2005
3. Hydro-Economic Models
NSF Interdisciplinary Modeling Workshop – July 2005
Hydro-economic Topics



Dam management balancing
hydropower, recreation, ecological
benefits
Administered water allocation
Policy-simulation, e.g.,
–
–
–
–
Auctioned access to locks
Targeted NPS abatement
Instream flow management
Economic forecasting of land use/hydrologic
change
NSF Interdisciplinary Modeling Workshop – July 2005
Example: Downstream Impacts of
Development (Johnston et al. JWRPM, 2006)
Determine the downstream economic value
of low-impact development:





Identify impact categories (flooding, water
quality,…)
Use weather series & HSPF to compute stage,
flow, and flood frequencies for different
development scenarios
Attach typical “prices” to impacts
Calculate economic impact of each scenario
Engineering costing of each scenario
NSF Interdisciplinary Modeling Workshop – July 2005
Example: Spatial Management of
Ag. Pollution (Braden et al., AJAE, 1989)
Max π = Revenues – Costs
s.t. Crop production functions
Spatial pollution transport
functions < T*
Identifies actions (crop, tillage) by
location that minimize economic
losses
NSF Interdisciplinary Modeling Workshop – July 2005
Hydro-economic Challenges
Scale: Markets vs watersheds
 Time: Water cycles vs Economic
cycles

NSF Interdisciplinary Modeling Workshop – July 2005
4. Bioeconomic Models
NSF Interdisciplinary Modeling Workshop – July 2005
Bioeconomic Topics
Fisheries management
 Floodplain & wetlands
management
 Forecasting landscape change and
effects on ecosystems

NSF Interdisciplinary Modeling Workshop – July 2005
Example: Efficient Protection of
Fish Habitat (Braden et al., WRR, 1989)
Max π (crops, tillage, pesticides)
s.t.
Prob {HSI (sed., chem.) > H*} > R
NSF Interdisciplinary Modeling Workshop – July 2005
Example: Economic/Runoff/Fish/Model
[Braden et al., WRR, 1989]
NSF Interdisciplinary Modeling Workshop – July 2005
Example: Cost/Habitat Suitability
[Braden et al., WRR, 1989]
NSF Interdisciplinary Modeling Workshop – July 2005
Fish Habitat: Discharges vs.
Impacts (Braden et al, AJAE, 1991)
Impact Targets:
Min C(x) s.t. Pr{q(x,h[x],ε)>Q} > A
Q = Habitat Qual., A = reliability
ε = stochastic factor
Discharge Standards (Proxy):
Min C(x) s.t. Pr {h(x) > H} > B
h intermed to q; H linked to Q
NSF Interdisciplinary Modeling Workshop – July 2005
Example: Habitat Impacts vs Discharges
[Braden et al., AJAE, 1991].
NSF Interdisciplinary Modeling Workshop – July 2005
Example: Floodplain Management
for Crops and Fish in Bangladesh
(Islam & Braden, Env. Devel. Econ., 2006)
MaxHi Σc,t φtNRcit*Hcit + Σf,t φtNRfi(qfit)*Hfit
s.t. ΣcHci + Σf Hfi < H all t [area]
qfit = gfit(Hfit) [nonlinear production]
Differentiates production functions by land
capability, crop, and species types
NSF Interdisciplinary Modeling Workshop – July 2005
Floodplain Model Implementation





Fourier analysis (econometric)
simulation of flood levels
Monthly average water levels -> flood
coverages w/ digital elevation model
Land capabilities identified
Capabilities changeable with levees
Optimize land allocations to activities by
max economic returns
NSF Interdisciplinary Modeling Workshop – July 2005
Bioeconomic Modeling Challenges
Matching spatial and temporal scales
 Model complexity
 Simplifications that lose information
(e.g., averaging)

NSF Interdisciplinary Modeling Workshop – July 2005
5. Benefit-Cost Models
NSF Interdisciplinary Modeling Workshop – July 2005
Policy Analysis

Maximum Net Benefits
– Potential Pareto Optimality – costs not
actually compensated
– Function of existing distribution

Discounting
– Opportunity cost of time

Max NPV =
Σt
{
(Benefits)t - (Costs)t
(1 + r)t
}
NSF Interdisciplinary Modeling Workshop – July 2005
6. Risk and Uncertainty
NSF Interdisciplinary Modeling Workshop – July 2005
Sources of Variability
Weather
 Ecological dynamics
 Geology/geography/topography
 Technology
 Households
 Culture
 Economy

NSF Interdisciplinary Modeling Workshop – July 2005
Modeling Variability
Statistical confidence intervals
 Monte Carlo simulation

NSF Interdisciplinary Modeling Workshop – July 2005
Challenges
Interactions of systems
 Differences in scale & detail
 Structural change
 Pure uncertainty

– Precautionary principle
NSF Interdisciplinary Modeling Workshop – July 2005
7. Summary Remarks
Economics adds people -systematically
 Total value vs. price & cost
 Integrating role
 Different disciplinary scales and
time-frames challenge integration

NSF Interdisciplinary Modeling Workshop – July 2005