Tradeoffs and Resource
Allocation Effects for
Alternative IS
Management Policies
Thomas Wahl, Zishun Zhao, & Ricardo Diaz
IMPACT Center and
School of Economic Sciences
Washington State University
www.impact.wsu.edu
The Rest Of The Team
• Preston Andrews, Horticulture
• Jan Busboom, Animal Science
• Ron Mittelhammer, Economics
• Ray Huffaker, Economics
• Michael Livingston, ERS
Motivation
Agricultural production is a complex and
dynamic process with an evolving productive
stock
 Changing demographics due to shocks
• BSE, FMD, coddling moth, …
 Long-lasting effects of these shocks
 Different effects on various participants
• Get the biological process right and then add
the IS shocks and policies
Objectives
• Develop a modeling framework that:
 Can be used to measure effects on social
welfare from IS
 Is general enough to accommodate
different animal and plant species
 Can establish the linkage between
economic loss and risk management
policies
 Will generate optimal resource allocation
schemes for alternative IS management
policies
Model Highlights
• Two bio-economic models
developed
 Animal Pest (Livestock model)
 Plant pest (Perennial fruit
model)
www.wsu.edu
www.nny.org
Model Highlights
• Inventories are differentiated by age
• Demand system
 AIDS
 Substitution effects
 Money-metric welfare measure
• Important IS pathways endogenized
• Flexibility in accommodating various
expectation schemes
Livestock Model
Non-Feed Fixed
and Variable Costs
Breeding Animal Imports
Feeder Imports
Price of Imports
Feed Price
Breeding
(Mature Female)
Import Costs
Breeding Stock
Nutrient Requirement
Sub-Model (Cow)
Retention
Constraints
Feed Cost
Initial Breeding
Stock and Feeders
Profit Maximization
Expected
Revenues
Offspring(M)
Expected price
Info available
Offspring(F)
Culling
Solution
Feeders
Culled Feeders
Culled Mature
Females
Expectations
Feedlot Optimization
Optimal Slaughter Weight
Average Slaughter
Weight of Cows
Finished Animal
Slaughter
Mature Animal
Slaughter
Non-fed Meat
Expected price
Exports
Fixed and
Variable Costs
Nutrient Requirement
Sub-Model (Feeder)
Fed Meat
Domestic Beef Market
Imports
World Beef Market
Exports
Domestic Prices
World Prices
Perennial Fruit Model
Interest and
Depreciation Rates
Wage Rates
Capital Cost
Labor Cost
Material Cost
Removal Cost
Profit Maximization
Planting Cost
Domestic Revenue
Info available
Material Prices
Export Revenue
Expected prices
Expectations
Solution
Constraints
Orchard
Fruit production
New Plantings
Low-production
blocks removal
Fruits
Domestic Market
Exports
Imports
Border Control
World Market
IS Introduction and Dissemination
• Production decisions in the presence of an
invasive species




Non-susceptible inventories
Immune inventories
Susceptible inventories
Affected (host) inventories
• Inventory groups determined by the dynamics
of dissemination
• Random nature of introduction and spread
IS Introduction and Dissemination (e.g.. livestock)
Introduction
Hosts
Susceptible
Immune
Non-Susceptible
Contact
Vaccination
Death and Depopulation
Hosts
Susceptible
Immune
Non-Susceptible
IS Introduction and Spread
• Establishment and spread
tj11    min{( t   tj ),( Kt j  tj )}  tj  tj  t
• Prevention—reducing the probability of
establishment and/or number of hosts
t
f (  t )  p (1  p)
H t  t
• Control—increasing the probability of
eradication
f ( t )   (1   )
t
X t j t
IS Introduction and Dissemination
• Introduction and eradication are random
variables with a geometric distribution
• Prevention—reducing the probability of
establishment
• Control—increasing the probability of an IS
being detected and eliminated
Policy Implications
• Prevention measures
 Marginal cost among measures equal
• Positive probability of establishment
 Eventually an IS becomes established
 Prolong interval between events
 Monitoring and emergency response
Policy Implications
• Tradeoff between prevention and control
 Resource use
 Fast-spreading, hard-to-eliminate species
• Preventing less costly
 Costly-to-detect, slow-spreading species
• Control less costly
• Confidence in government agencies
 Producers perception of susceptibility will
change probability of becoming affected
Livestock Model Implementation
• Annual beef production model with 9-year
reproductive life
• Feeders go through backgrounding and a
fixed ration feeding program
• Growth and body composition of feeders
predicted using NRC nutrient requirements
• Quality and yield grade predicted to fit the
marketing system grid
• Linear search to determine the optimal
slaughter point
Livestock Model Implementation
• Demand for both fed beef and cow beef
• Inventory updating—naïve expectations in unit
profitability with partial adjustment
 Unit profitability as a proxy for capital value
of cows
Simulated Scenarios
• Assumed scenarios to test the validity and
stability of the model
 One-time 30% reduction in breeding herd
representing a dramatic depopulation
 15% death rate in the breeding herd
representing an epidemic
 100% increase in the feed cost
representing feed regulation
 100% increase in breeding cost
(maintenance cost of cows)
One-time 30% Inventory Reduction
6
Simulated Prices
5
Base
30% Depopulation
4
3
2
1
11
21
31
45
41
51
61
71
81
91
71
81
91
Simulated Breeding Stock
40
35
30
25
20
1
11
21
31
900
41
51
61
Simulated Finished Weight
850
800
750
1
11
21
31
41
51
61
71
81
91
Death Rate Increase to 15%
8
6
Base
4
15% Death
Simulated Prices
2
1
11
21
31
41
51
61
71
81
91
45
Simulated Breeding Stock
40
35
30
25
1
11
21
890
31
41
51
61
71
81
71
81
91
Simulated Finished Weight
870
850
830
810
790
770
1
11
21
31
41
51
61
91
100% Increase in Feed Cost
4.0
Base
Double Feeding Cost
Simulated Prices
3.5
3.0
2.5
1
11
21
31
45
41
51
61
71
81
91
Simulated Breeding Stock
40
35
30
1
11
21
31
900
41
51
61
71
81
91
Simulated Finished Weight
850
800
750
700
650
600
1
11
21
31
41
51
61
71
81
91
101
100% Increase in Breeding Cost
8
Base
Double Breeding Cost
Simulated Prices
6
4
2
1
11
21
31
45
41
51
61
71
81
91
71
81
91
71
81
Simulated Breeding Stock
40
35
30
25
20
15
1
11
21
31
950
41
51
61
Simulated Finished Weight
900
850
800
750
1
11
21
31
41
51
61
91
Simulation of FMD w/o Intervention
• Assuming no treatment and full recovery
• Dissemination rate of 4 herds/week
• 2% death in mature cattle and 20% death in
calves
• Normal demand continues
FMD Scenarios With Normal Demand
4.5
Prices
Normal Dmenad
FMD Free
4.0
3.5
3.0
2.5
2.0
1
11
21
31
41
35.5
35.0
34.5
34.0
33.5
33.0
32.5
32.0
61
71
81
91
101
Breeding Herd
1
6
5
4
3
2
1
0
-1 1
-2
51
11
21
31
41
51
61
71
81
91
Profit
11
21
31
41
51
61
71
81
91
101
Progress of the Perennial fruit model
• A simulation model for apple production is
being implemented
• Increasing marginal cost is assumed
• Formulated as a mixed complementarity
problem
• Runs of a preliminary version show stable and
reasonable solutions
Summary and Conclusion
• Dynamic general equilibrium framework
captures short- and long-term effects
• Linkage between the economic loss and the
risk management policies
 Cost-benefit analysis
 Optimal resource allocation
• Validity and stability demonstrated
Unresolved Issues and Possible Extension
• Welfare measure for the producers
• A simulation model incorporating all livestock
production
 Common diseases
 Substitution effects
• A livestock model including Canada, the US,
and Mexico where all the live trade occur
Conference Papers
• Zhao, Zishun, Thomas Wahl, and Ricardo Diaz. “Modeling the
•
•
Effects of Alternative Invasive Species Management Policies on
livestock Production.” Selected long paper, AAEA 2004, Denver,
CO.
Zhao, Zishun, Thomas Wahl, and Ricardo Diaz. “Modeling the
Impacts of Alternative Invasive Species Management Policies on
Perennial Fruit Production and Consumption.” Selected paper,
WAEA 2004, Honolulu, HI.
Díaz, Ricardo, Thomas Wahl and Zishun Zhao. “The Economic
Implications of Invasive Species in International Trade: The Chile
– US Fresh Fruit Market.” Paper Presented to ASCC, PECC Trade
Forum – LAEBA Conference 2004, Viña del Mar, Chile
Tradeoffs and Resource
Allocation Effects for
Alternative IS
Management Policies
Thomas Wahl, Zishun Zhao, & Ricardo Diaz
IMPACT Center and
School of Economic Sciences
Washington State University
www.impact.wsu.edu