Download Translating invasive species science into policy

Translating invasive species
science into policy
Kimberly Burnett, University of Hawaii
n


 rt
MAX  e   c( )d   D(n)  dt
0
 n- x


n  g ( n)  x
0 xn
n 0 given
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.
How fast does it grow?
g(n)
Island
K
Kauai
15,849,057
Oahu
8,713,551
Maui
14,133,791
Hawaii
78,216,124
Molokai
3,087,479
600000
500000
400000
300000
200000
100000
0
n
0
2000000
4000000
6000000
8000000
n

g (n)  bn 1  
 K
Where K = 100 trees per acre above
1800 mm/yr rainfall line, b = 30%
Where is it?
Tells us potential damage
The value of losing
birds & water
mgd lost
recharge
(annual)
Island
# birds
Low
Total annual damages by island
(millions)
High
Low
Medium
High
Kauai
22
3.2
3.9
$91.6
$154.0
$234.0
Oahu
13
3.2
3.9
$61.4
$98.5
$145.0
Maui
17
3.7
4.6
$77.8
$126.0
$187.0
20
18.0
22.0
$169.0
$225.0
$297.0
11
N/A
N/A
$36.9
$68.2
$108.0
Big Island
Molokai
Per tree damage
Island
Medium annual damages/K
Kauai
$9.74
Oahu
$11.30
Maui
$8.93
Hawaii
$2.88
Molokai
$22.09
Cost of control?
Island
Search Constant
($1000*acre)
Search Coefficient Treatment
Coefficient
()
Kauai
$158,490,570
1.6095
Oahu
$87,135,510
1.6258
Maui
$141,337,910
1.6089
Big Island
$782,161,240
1.6028
Molokai
$30,874,790
1.6
 $1, 000*potential acres

c(n, x)  

13.39
* x

n


$13.39
Current population?
Island
n
Kauai
1,540
Oahu
6,890
Maui
111,050
Hawaii
315,000
Molokai
0
0
Optimal population
Island
n
0
n*
Kauai
1,540
9,171
Oahu
6,890
5,495
Maui
111,050
8,901
Hawaii
315,000
39,937
Molokai
0
0
Policy comparisons
Island
Policy
Do nothing
Remain at
current population
forever
Status quo
spending
Optimal policy
of population reduction
and maintenance
Oahu
$3.08 b
$10.5 m
$16.9 m
$10.4 m
Maui
$4.6 b
$73.5 m
$51.7 m
$17.2 m
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.).
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
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
Outlier,
excluded
(over 100,000 ac)
Percentage of transactions
with frog complaints prior to sale
Region
Average
Price
Frogs
500m
Frogs
800m
Average
Acres
N. Obs.
Puna
$26,555
19.3%
34.1%
2.6
24,019
S Hilo
$126,141
5.7%
23.2%
10.8
4,443
N Hilo
$283,383
7.0%
7.0%
18.2
633
Hamakua
$154,732
10.0%
25.5%
38.2
928
N Kohala
$202,599
33.7%
42.9%
10.4
1,758
S Kohala
$409,796
37.3%
48.4%
6.8
3,479
N Kona
$334,393
13.2%
33.9%
2.9
6,733
S Kona
$773,204
23.5%
40.6%
21.7
2,064
Kau
$25,179
15.1%
23.8%
8.7
5,981
Puna Close-up
Frogs within 500 m
Frogs within 800 m
Transactions
Impact on Property Price
Variable
Frogs 500m
Frogs 800m
Frogs
-135,957***
(19327)
-6,816
(7845)
SFLA
67***
(4)
64***
(4)
Assessed Land Val
0.5***
(0.2)
0.5***
(0.2)
Acres
471**
(190)
474**
(191)
Mortgage rate
(monthly)
-25,494***
(4043)
-17,237***
(3917)
Buyer in HI
-24,981***
(9470)
-24,969***
(9479)
Constant
212,062***
(28833)
139,301***
(27384)
Number of observations
Adj R2
50,033
50,033
0.2
0.2
***,** indicate statistical significance at 99% and 95% confidence respectively
Huber-White Robust Standard errors in parentheses.
Recap
• Presence of frogs have a negative impact on property value
• Tells us nothing about optimal policy (don’t know the response
of population to spending)
• Need to build model
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
Acknowledgements
Special thanks to Earl Campbell, Mindy Wilkinson, and Christy Martin
for answering zillions of questions!