barry k. goodwin nicholas e. piggott north carolina state university

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The Feasibility of The Feasibility of Indemnification and Check- Indemnification and Check- off Funded Programs to off Funded Programs to Manage Invasive Species Manage Invasive Species Risks in Agriculture Risks in Agriculture Report of Progress Report of Progress Barry K. Goodwin Nicholas E. Piggott North Carolina State University

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The Feasibility of Indemnification and Check-off Funded Programs to Manage Invasive Species Risks in Agriculture Report of Progress. Barry K. Goodwin Nicholas E. Piggott North Carolina State University. Overview. - PowerPoint PPT Presentation

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The Feasibility of Indemnification The Feasibility of Indemnification and Check-off Funded Programs and Check-off Funded Programs

to Manage Invasive Species Risks to Manage Invasive Species Risks in Agriculturein Agriculture

Report of ProgressReport of Progress

Barry K. Goodwin

Nicholas E. Piggott

North Carolina State University

OverviewOverview

Increased integration of world markets & international mobility of goods and people•heightened concerns regarding harmful invasive species

Threat is substantial to agriculture & some significant damages have already been realized in U.S. agriculture

Overview…Overview…

Current response has been to provide ad hoc disaster assistance targeted to specific commodities and/or regions

An alternative strategy might involve either a fund or insurance program to protect producers from risks associated with specific invasive specifies

Objectives: Two FoldObjectives: Two Fold

Evaluate economic issues in design of voluntary insurance and mandatory check-off programs

Statistical modeling of the risks associated with several case studies with the aim of pricing insurance or determining optimal check-off contribution rates Case studies: Asiatic canker, karnal bunt, and

soybean rust

Objectives….Objectives….Model contamination risks and expected losses at

county level for a representative producer

Attention to exogenous factors associated with transmission including Trade and transportation patterns Migrant labor and harvesting crews Important characteristics of land and farms Weather

Statistical models explicitly measure spatial patterns of risks and transmission

Uncertainty of the RiskUncertainty of the Risk• Harmful economic effects of an infestation

or contamination by a NIS are similar to effects of any other pest or disease–Exposure may lead to yield losses or affect quality (crops and livestock)

• What is different is the uncertainty associated with the risks from many different known and unknown pests and diseases–Potential for catastrophic losses from new NIS may far exceed losses from more common pests and diseases

State of AffairsState of Affairs• Congress typically responds to losses from outbreaks of pests and disease by providing direct ad hoc payment to affected producers –E.g. $32 m on karnal bunt in wheat in 1990s–Some states also provide financial assistance

• Costs of prevention and managing spread of diseases and outbreak impose large cost on govt

“if the CCC fund cannot be accessed, then we need to consider the development of an invasive pest trust fund” (Carl Loop, President FL Farm Bur., congressional testimony (Jan 2000)

Indemnification ProgramsIndemnification Programs• Feasibility and operational aspects of a

program for indemnifying producers against specific perils–current programs may not be entirely comprehensive and sufficient• e.g, Citrus canker can involve multi-years of

loss in a grove;

Indemnification Programs…Indemnification Programs…

• Two options are considered:–Mandatory program that operates using a “check-off” on production, all producers pay into a fund used to cover losses• might also fund prevention/eradication

programs–Voluntary indemnification program that measures risks relevant to a specific threat and provides coverage• “additional insurance” beyond what is

already available

Usefulness of this WorkUsefulness of this Work

• Should be of interest to state and federal policymakers currently faced with developing ways to manage these risks

• An indemnification involving insurance or check-off could be independent of government support or partially subsidized

• These “self-help” alternatives recognized that some of the risk should be internalized (or borne) by those who have the most to lose and not entirely borne by the taxpayer

Premium or Check-off Rate Needed to Premium or Check-off Rate Needed to Cover Expected Losses?Cover Expected Losses?

• Under both scenarios the key parameter is the appropriate premium or check-off rate that will cover expected losses

• We are developing and evaluating methods of measuring the risks associated with these losses

• Analogous to deriving measures of the actuarially fair insurance rate that would be needed to operate a specific peril program

Research MethodsResearch Methods• Measuring the risk requires measuring the

probability density underlying risks (e.g., yield losses due to the specific peril under consideration)

Yield

Prob.

Indemnities & CostsIndemnities & Costs

• For a program that reimburses producers for yields (y) that are beneath a certain proportion () of their expected (mean) yield ()

Indemnities = p. (max{ ( - y), 0})

p the price at which losses are compensated

Premium or Check-off RatePremium or Check-off Rate• Insurance program or check-off requires a premium

or mandated contribution rate determined by expected payouts

• For p=1, expected loss is given by

E(L)=Prob(y<)*[-E(y|y<)]

• Define F() and f() to be the cumulative probability distribution functions (cdf) and the probability density function (pdf)

Premium or Check-off RatePremium or Check-off Rate

• E(Loss) = Pr(loss)*(Loss|Loss Occurs)

• Define F() and f() to be the cumulative probability distribution functions (cdf) and the probability density function (pdf) and the premium or check of rate (R) can be shown to be equal to

0

0

0

0

( )( ) ( )

( )

( ) ( )

( )

( )

f y ydyE Loss f y dy

f y dy

f y ydyF

F

E LossR

Economics of Check-off Funded Economics of Check-off Funded Prevention/eradication ProgramPrevention/eradication Program

b

c

D

D’

S’

S

Q’ Q

P

P’ Gains in Total Economic Surplus

S+T a

e f

g h

l m n

d

j

k i

o

p

P’’

Q’’

q r

s

t

Price

Quantity

E E’

E’’

Challenging Modeling QuestionsChallenging Modeling Questions• What is the appropriate form of the

distribution [f(y)]?• Are parametric densities appropriate or

less restrictive techniques preferred?• What factors should the distribution be

conditioned on?• What are the spatial-temporal relationships

associated with the invasive species?

Case Study: Citrus Canker in FLCase Study: Citrus Canker in FL

• Large concern to Florida citrus• Threat since 1910s but outbreak in

residential citrus trees in Dade county in Sept of 1995– Triggered widespread quarantines and mandatory destruction of citrus stocks

– Over 1.3 million trees destroyed• Spatio-temporal aspects of transmission

especially interesting for evaluating risk

Source: Gottwald et. al. (2001)

Spatio-Temporal Impacts of Spatio-Temporal Impacts of yyi,t

t=1

t=3t=4

t=2

i=9

yz

f(yz)

Model to Estimate the Density Model to Estimate the Density Functions in a Localized Area Functions in a Localized Area

, , , , , ,

,

County Probability Density Functions f( )

( ) ( , , , ) +

1, 2, ........ ( )

1, 2, ........ ( )

vector of exogenous factors

error term

i

i t i t i t k j t j t k i t

i t

y

f y f y y y y

where

i N counties

t T periods

θ

θ

Modeling IssuesModeling Issues

• Spatio-temporal correlation:–Contamination spreads along avenues characterized and influenced by spatial and temporal characteristics

–Common analysis in epidemiological studies

• The process is likely to be characterized by models with large numbers of parameters

• We will address this using hierarchical models which consider stages or layers of relationships

Modeling Issues….Modeling Issues….• We likely will adopt a mixture distribution model that

recognizes different states of nature (e.g., recent or nearby infection versus no obvious infections)

• Similar models have been applied to model catastrophic versus “normal” crop risks (Goodwin and Ker)

• Our analysis will be conducted in a Bayesian context using diffuse priors and the model fitting criterion proposed by Gelfand and Ghosh

Modeling Issues….Modeling Issues….

• Account for the catastrophic risk associated with spread through a significant hurricane event (a significant catalyst for infection spread)

• This has not been observed in our data and thus we must assume “tail” probabilities that are associated with events that are nontrivial in probability but that have not been experienced–historical hurricane records (data that we have already assembled)

Florida DataFlorida Data• We traveled to Florida in April to learn about citrus

canker (transmission, damaged, current eradication program etc)

• Met with representatives of citrus canker eradication program, USDA, and Florida Dept. of Ag. (Tim Gottwald, Tom Gates, Fritz Roka)

• Recently received authorization (lengthy process)• On July 29 we received an initial dataset of

commercial grove data (inspection results at the sub-grove unit level)

Other ApplicationsOther Applications

• Methodology and techniques being developed are general and can be applied to other spatio-temporal risks of invasive species–e.g. spread of soybean rust rising concern in North Carolina with new import facility in Wilmington

• We may shift focus of second application to rust rather than karnal bunt as we were notified that the “karnal bunt pest risk assessments (basis for data) are still in draft format and not ready to be released”