Pest Control

1. PestControl David Zilberman ARE 253 PP253

2. Pesticides: Damage Control Agents • Pests include: • Big animals (elephants, coyotes) • Small creatures (mice, birds) • Insects • Viruses • Weed • Control types--Chemical • Agronomic: fences,hoes, tractors, traps • Biological: cats, dogs, predators of pests • Seed varieties including genetically modified crops: pest resistant, pesticides tolerant

3. Modeling Pest-Control Choices • 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

4. Pest Population and Pest Control • 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.

5. Preventive vs. Responsive Application • 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.

6. Effective Pest Management & Biology • Predator-prey consideration • 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.

7. Resistance • 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. • Use regulation to limit the use of materials to “worthwhile“ situations. • Research to identify alternatives.

8. One Person’s Pest Is Another Person’s Game • The definition of pests is relative: • Elephants damage farms but can be a source of eco-tourism 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.

9. Health Risks of Pesticides • Food safety—mortality or morbidity resulting from chemical residues—include: • 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: • Damages to fish, birds, beneficial insects. • Some pesticides are possible or definite endocrine disrupters (block the action of male hormones).

10. Controlling Pesticide Externalities • 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.

11. MC=Marginal Cost MB=Marginal Benefit MEC=Marginal Externality Cost MRC=Marginal Resistance Cost Social optimum=point A Monopoly =Price C Quantity B Competitive outcome=point E Possible Pesticide Use Levels Price Demand MB of production Monopoly Price C Marginal revenue MC +MRC+MEC A MC E Quantity B

12. Possible Use Levels of Pesticides • 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.

13. Pesticides in Developing Countries • Under-application in some situations. • 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). • Safety rules may not be followed, and there are cases of overappliation.

14. Reasons for overappliction • 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.

15. The Good and Bad Sides of Pesticide Use • 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.

16. From Chemicals to GMO • 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.

17. Expected Yield Effects of Pest-Resistant GM Crops in Different Regions

18. A General Problem: Policies to Control Environmental Risks • 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.

19. Properties of Risk Assessment Models • 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 • Human health risk • Environmental health risk (risk to fish) • Food security

20. Chemical Application Risk Pollution control policies Barriers/filters Protective clothing Medical treatment Risk Contamination Exposure Dose/ Response * Transfer& 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 in case of poisoning and injury.

21. Farm Worker Pesticides Risk • 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.

22. Modeling Environmental Risk • 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 importantin this context). • These processes are controlled through policies.

23. Policy Optimization under Risk • A reasonable policymaking principle- • The objective is to maximize economic welfare subject to the constraint • Probability (Risk < R) >  • R = target level of risk • . = safety level (measures the degree of social risk aversion)  might represent the degree of confidence we have in our risk estimate. • For example, policymakers may aim to maximize economic surplus given that risk from pesticides cannot exceed 1 million with a 95% probability.

24. Uncertainty and Assessment • 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.

25. Sources of Variability • Coefficients of risk-generation functions vary. • We may not have a reliable number representing coefficients of specific processes. • The risk function may be r = a* b* g *X and the coefficients may be stochastic. • The causes of variability: • Heterogeneity can be handled by more specific analysis. • Randomness. • Uncertainty (lack of knowledge) can be reduced by learning.

26. Pesticide Registration • 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.

27. Pesticide “Doctors” • 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.