Translating invasive species science into policy

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Translating invasive species science into policy

• Kimberly Burnett, University of Hawaii

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Outline
All Miconia photo credits K.
Burnett, near Hana
Coqui sushi photo credit NWRC Hilo, HI

• Miconia how much damage? Depends on policy.
• Working with nonmarket values.
• Coqui frogs damage to property values (no
  policy analysis).
• Market values.
• My hope elucidate the VALUE of good scientific
  data in economic modeling.

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How fast does it grow?
Where K 100 trees per acre above 1800 mm/yr
rainfall line, b 30
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Where is it? Tells us potential damage
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The value of losing birds water
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Per tree damage
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Cost of control?
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Current population?
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Optimal population
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Policy comparisons
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Recap

• Population reduction optimal for most islands.
• For Oahu, close to the optimal population (just
  above). Spend more today to reduce population,
  then can spend less every year to keep it there
  (cut the growth every year). Strategy saves on
  future damages.
• Better data better understanding of
  growth/cost/damage functions better model of
  response of population to spending better
  policy less damage.
• Difficulty with nonmarket valuation (true value
  of endangered birds, etc.).

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Falling property prices?Hedonic pricing theory

• Wish to explain determinants of total property
  price
• Some things add to price, others subtract
• Structural
• Number of rooms, number of bathrooms, square
  footage ()
• Acreage ()
• Neighborhood/Accessibility
• Proximity to public transportation, school
  districts, other amenities (/)
• Zoning (/)
• Environmental
• Presence of coqui (???)
• Elevation ()
• Financial
• Mortgage rates ()
• Buyer in HI ()
• Derive implicit value of each characteristic from
  explicit price of property using multiple
  regression analysis

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Study site and data

• 50,033 real estate transactions on Big Island,
  1995-2005
• 9 main districts (see map) divided into 10
  sub-districts each to control for neighborhood
  characteristics
• SFLA to represent structure
• Frog complaints registered to NWRC Hilo,
  1997-2001
• Use GIS to identify property transactions
  occurring after complaint, within 500m and 800m
  of frog complaints
• Financial variables
• Prices deflated using West Urban CPI
• 30 year mortgage rates from Federal Reserve
• Buyer residing in HI used to control for
  information effects

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Outlier, excluded (over 100,000 ac)
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Percentage of transactions with frog complaints
prior to sale
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Puna Close-up
Frogs within 500 m
Frogs within 800 m
Transactions
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Impact on Property Price
, indicate statistical significance at 99
and 95 confidence respectively Huber-White
Robust Standard errors in parentheses.
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Recap

• Presence of frogs have a negative impact on
  property value
• Tells us nothing about optimal policy (dont know
  the response of population to spending)
• Need to build model

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Directions for future research

• Miconia
• Better data on current number of trees on each
  island, growth, costs, locations
• Coqui
• Real estate analysis increase years of BI data,
  add Maui data
• Calculate lost profits to horticultural industry
  from
• Reduced revenues from lost sales if infested
• Increased costs from removing frogs for
  certification
• Model the increase in potential viability of
  brown treesnake and accompanying increase in
  potential damages (biodiversity loss, power
  supply and medical expenses) due to coqui prey
  base

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Acknowledgements
Special thanks to Earl Campbell, Mindy Wilkinson,
and Christy Martin for answering zillions of
questions!