The Feasibility of Indemnification and Check-off Funded Programs to Manage Invasive Species Risks in Agriculture Report of Progress

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The Feasibility of Indemnification and Check-off
Funded Programs to Manage Invasive Species Risks
in AgricultureReport of Progress

• Barry K. Goodwin
• Nicholas E. Piggott
• North Carolina State University

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Overview

• 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

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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

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Objectives 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

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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

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Uncertainty 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

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State 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)

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Indemnification 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

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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

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Usefulness 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

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Premium or Check-off Rate Needed to 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

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Research Methods

• Measuring the risk requires measuring the
  probability density underlying risks (e.g., yield
  losses due to the specific peril under
  consideration)

Prob.
Yield
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Indemnities Costs

• For a program that reimburses producers for
  yields (y) that are beneath a certain proportion
  (l) of their expected (mean) yield (m)
• Indemnities p. (max (l m - y), 0)
• p the price at which losses are compensated

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Premium or Check-off Rate

• Insurance program or check-off requires a premium
  or mandated contribution rate determined by
  expected payouts
• For p1, expected loss is given by
• E(L)Prob(yltlm)lm-E(yyltlm)
• Define F() and f() to be the cumulative
  probability distribution functions (cdf) and the
  probability density function (pdf)

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Premium or Check-off Rate

• E(Loss) Pr(loss)(LossLoss 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

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Economics of Check-off Funded Prevention/eradicati
on Program
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Challenging 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?

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Case 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

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Source Gottwald et. al. (2001)
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Spatio-Temporal Impacts of yi,t




f(yz)
i9
yz








t1
t2








t3
t4
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Model to Estimate the Density Functions in a
Localized Area
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Modeling 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

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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

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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)

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Florida 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)

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Other 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