Pest control

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Transcript Pest control

Pest Control
David Zilberman
ARE 253 PP253
7/21/2015
Pesticides: Damage Control Agents
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Pests include:
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Big animals (elephants, coyotes)
Small creatures (mice, birds)
Insects
Viruses
Weed
Control types--Chemical
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Agronomic: fences,hoes, tractors, traps
Biological: cats, dogs, predators of pests
Seed varieties including genetically modified crops:
pest resistant, pesticides tolerant
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Modeling Pest-Control Choices
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Y = OUTPUT Z = INPUT (fertilizer)
Q = g(Z) - potential output
X = pesticides-damage control agent
d(N) = fraction damaged, N = final pest population
N = h(X, M) M = initial pest population, pesticides reduce
population from M to N
Y = g(Z)*(1 - d(h(X))
Firms aim to maximize profits
P = output price, W = input price, V = pest-control price
A = fixed application cost
Profit = Pg(Z)*(1 - d(h(X,M)) - Z*W - V*X - A
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Pest Population and Pest Control
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At optimal solution
VMPZ = P(∂g/ ∂ Z) *(1 - d(n(X,M)) = W.
Value of marginal product of input = input price.
VMPX= -P g(Z)*∂d/∂N *∂n/∂X = V.
Value of marginal product of pest control = its price.
Larger initial population requires more application.
If initial population is sufficiently small and does not cover
fixed application cost, do not apply.
Application is warranted if a population threshold has
exceeded. Apply only if M > threshold.
Estimation population is costly.
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Preventive vs. Responsive Application
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Pest population arrival time and size are random.
Preventive applications. Based on average performance;
may lead to overspraying. Standard spraying based on a
large population will occur when pests do not arrive or
population is small.
Responsive application requires costly monitoring of
population; will save chemicals but require costly
monitoring and may lead to slow or incomplete response to
invasion.
Integrated pest management. Relies on monitoring of pest
population and combines a mixture of strategies that aim to
minimize use of chemicals.
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Effective Pest Management & Biology
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Predator-prey consideration
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Suppose two pests cause damage, and N1 & N2
denote their populations.
Pest 1 is the predator of 2 so
N1 = n1(X1, M1) & N2 = n2 (N1, M2)
The optimal rule for applying pest control 1 -X1
VMPX1= MCN2 + V
The value of pesticides in controlling pest 1 = marginal
cost of larger population of pest 2 + pest control cost.
Control of pests that are also predators of other
pests should recognize their benefits and reduce
application levels accordingly.
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Resistance
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Occurs when efficacy of pesticides declines as use
of chemical increases over time.
Since pests move across farms, it is a common
problem. Individual producers ignore future
resistance cost associated with pesticides use.
Policy intervention
(Ideally) Incentives (tax or subsidy) to reflect the
social cost of resistance.
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Use regulation to limit the use of materials to
“worthwhile“ situations.
Research to identify alternatives.
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One Person’s Pest Is Another
Person’s Game
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The definition of pests is relative:
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Elephants damage farms but can be a source of ecotourism income.
Feral pigs cause damage to field crops, but many
will pay to hunt them.
Pest management strategies should take
advantage of strategies that will take advantage
of pests and reduce the cost of pest control.
The beneficiaries of “green” pest control
methods should pay to support them.
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Health Risks of Pesticides
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Food safety—mortality or morbidity resulting from
chemical residues—include:
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Acute impacts—poisoning, allergic responses.
Poisoning when packaging materials used for food
consumption
Chronic impacts—cancer.
Much uncertainty about the food safety effect.
Worker safety—damage to mixer applicator and
farmers may be high, especially if caution is not taken.
Environmental safety:
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Damages to fish, birds, beneficial insects.
Some pesticides are possible or definite endocrine
disrupters (block the action of male hormones).
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Controlling Pesticide Externalities
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Registration requirements. Before a product is introduced,
it must pass a battery of test to identify obviously risky
products (carcinogens).
Incentives. Taxes and subsidies to pay for damages.
Limits on total use. Tradable permits to users.
Ban. Complete or partial bans on chemicals?.
Restrictions on applications. Limits on when, where, and
how chemicals are applied (e.g., not near schools, when it is windy,
or aerially spraying).
Direct control. Protective clothing, food treatment
requirements, and reentry regulation to sprayed fields.
Education and information. Notification regarding
spraying activities and possible exposure risks.
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Possible Pesticide Use Levels
Price
Social optimum=point A
Monopoly =Price C Quantity B
Competitive outcome=point E
Monopoly
Price
Demand
MB of production
E
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MEC=Marginal
Externality Cost
MC +MRC+MEC
A
B
MB=Marginal Benefit
MRC=Marginal
Resistance Cost
C
Marginal
revenue
MC=Marginal Cost
MC
Quantity
Possible Use Levels of Pesticides
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If a manufacturer is a monopoly (has a patent),
there may be under-use of pesticides if a
monopoly price hike is greater than marginal
externality and resistance costs.
Social optimum occurs if marginal benefits of
pesticides in production equals sum of marginal
externality, resistance, and production cost.
Without intervention, the most use occurs where
marginal benefits equal marginal cost of
production.
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Pesticides in Developing Countries
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Under-application in some situations.
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Many developing countries are in the humid tropic with major
pest problems, but not many have pest control tools, since most
pesticides have been developed for problems in developed
countries and temperate zones.
Adaptation of pest control solutions is costly, and ability to pay
for companies’ investment are limited.
Pesticide application equipment is costly, and peasants
frequently face credit constraints.
Techniques such as bio-control (mealybug in cassava) and
GMOs are especially useful (and easy to apply and spread).
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Safety rules may not be followed, and there are cases of
overappliation.
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Reasons for overappliction
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There is lack of enforcement of environmental
regulation, resulting in overuse and exposure.
Pesticide patents may not be registered or
recognized, and cheap old generic ones are used.
Pesticides may be subsidized in some countries
(China).
Cheap materials may be combined with cheap
application equipment, and unregulated setup will
lead to environmental dangers.
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The Good and Bad Sides of Pesticide
Use
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Average pest losses in Indian cotton are 50-60%. Insect
pests losses In the United States and China are 12% &15%,
respectively. It’s climate & less pesticides.
Yield-increasing pesticides may prevent deforestation and
acreage of farming.
The low productivity effect of pesticides in rice in the
Philippines and Indonesia, combined with worker safety
effects, suggests much overuse there.
Banning chemicals in most cases is suboptimal. The
problem is not chemicals but how they are being used.
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From Chemicals to GMO
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Pesticide regulations have triggered introduction of new
chemicals and GMOs.
Bt cotton has reduced pesticide applications in US and
china by 50-60%,but yield effects are between 0-5%. In
India yield effects are +50%.
The high pest pressure in developed countries and lack of
pesticides suggest high yield-increasing potential for
GMOs.
Effort in adaptation and development of appropriate
genetic materials and access to Intellectual Property
Rights are needed.
Possible externalities need to be inspected.
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Expected Yield Effects of Pest-Resistant GM
Crops in Different Regions
Adoption
Pest
Alternatives
of
Yield
pressure
Availa bility
alternatives
effect
Developed
countries
low to
medium
high
high
low
Latin A merica
(commercial)
medium
medium
high
low to
medium
China
medium
medium
medium to
high
medium
Latin A merica (noncommercial)
medium
medium
low
medium
to high
South and
Southeast Asia
high
ow to
medium
low to
medium
high
Africa
high
low
low
high
Region
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A General Problem: Policies to
Control Environmental Risks
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The impacts of policies are uncertain, and the environment
is subject to stochastic forces.
Methodologies to both model risk and analyze choices
under risk are crucial for effective policymaking.
There are alternative approaches to risk. Economic and
decision theoretic models measure risk as deviations from
the norm or average. They emphasize assessing the impact
of such deviations on behavior and their cost.
Public health develops risk assessment techniques that
define risk explicitly as the probability of data outcome.
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Properties of Risk Assessment Models
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Risk = probability that a member of a population will
die or get sick during a period of time.
Risk-generating functions = relationship between risk
and processes that cause it.
The knowledge needed for risk-generation functions is
interdisciplinary. It provides the base for both
estimation and policymaking.
Risk assessment models can be used to assess
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Human health risk
Environmental health risk (risk to fish)
Food security
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Chemical Application Risk
Pollution control
policies
Risk
=
Barriers/filters
Contamination
Protective
clothing
Medical
treatment
Dose/
Transfer&
Exposure
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* Response
fate
Risk of chemical residues can be reduced by
*Reducing application levels through taxes, direct
control,etc.
*Blocking movement of residue to and in bodies of water
(can be induced by incentives).
*Reducing human exposure by filters,protective clothing.
*Treatment
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Farm Worker Pesticides Risk
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Let r = represent individual health risk where
r = f1(X,B1) f2(B2)
f3(B3)
initial exposure exposure dose/response
X = pollution on site (i.e., the level of pesticide use)
B1 = damage control activity at the site (i.e., protective
clothing; re-entry rules)
B2 = averting behavior of individuals (i.e., washing fruits
and vegetables)
B3 = the medical control of pollution dosage.
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Modeling Environmental Risk
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The modeling principles used to model human
health risk from pesticides also apply to modeling
risk to, say, birds.
There are processes of contamination transfer and
fate exposure and dose response (transfer and fate and
contamination are most important in this context).
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These processes are controlled through policies.
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Policy Optimization under Risk
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A reasonable policymaking principleThe objective is to maximize economic welfare
subject to the constraint
Probability (Risk < R) > 
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R = target level of risk
. = safety level (measures the degree of social risk
aversion)
 might represent the degree of confidence we have in our
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risk estimate.
For example, policymakers may aim to maximize
economic surplus given that risk from pesticides cannot
exceed 1 million with a 95% probability.
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Uncertainty and Assessment
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Use of higher degree of statistical reliability, 
leads to higher risk estimate. The risk of a chemical
may not increase .05 with = .95, but may
exceed it with = .995 .
Is useful to use consistent reliability requirements
for all risk estimates to allow comparisons.
It may be useful to identify a target group in the
population (say, top 95% in terms of vulnerability)
and compare how policies affect risk to this group.
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Sources of Variability
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Coefficients of risk-generation functions vary.
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We may not have a reliable number representing coefficients of
specific processes.
The risk function may be r =  * b * g *X and the coefficients
may be stochastic.
The causes of variability:
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Heterogeneity can be handled by more specific analysis.
Randomness.
Uncertainty (lack of knowledge) can be reduced by learning.
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Pesticide Registration
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Main form of policy is pretesting and registration.
Objective is to eliminate “risky” pesticides and minimize
side effects.
Once a product is discovered to be problematic, it may be
banned or its use restricted.
Intensive testing is beneficial to corporations because it
increases entry costs ($50+ million to introduce a new
chemical) and assures their market power.
It reduces availability of new products and results in
“orphan” diseases, especially used in specialty crops and
developing countries.
Governments and donors may need to subsidize
introduction of new products beneficial to society but not
to private sectors.
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Pesticide “Doctors”
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Productivity of pesticides can be enhanced, and their
environmental impact reduced if their performance is
monitored and decisions on what and when to apply
are optimized.
One approach is to restrict diagnosis of pesticides to
certified pesticide consultants and applications to
certified applicators.
Extension can train both types of professionals. They
can also be required to document pesticide applications
and may be liable for wrong choices.
Optimal sharing of liability for mistakes is a challenge,
but if done correctly can improve policy.
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