Translating invasive species

science into policy

Kimberly Burnett, University of Hawaii

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Outline

• 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.

Coqui sushi photo credit: NWRC Hilo, HIAll Miconia photo credits: K. Burnett, near Hana

How fast does it grow?

( ) 1n

g n bnK

Island K

Kauai 15,849,057

Oahu 8,713,551

Maui 14,133,791

Hawaii 78,216,124

Molokai 3,087,479Where K = 100 trees per acre above 1800 mm/yr rainfall line, b = 30%

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100000

200000

300000

400000

500000

600000

0 2000000 4000000 6000000 8000000n

g(n)

Where is it? Tells us potential damage

The value of losing birds & water

mgd lost recharge (annual)

Total annual damages by island (millions)

Island # birds Low 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

Big Island 20 18.0 22.0 $169.0 $225.0 $297.0

Molokai11 N/A N/A $36.9 $68.2 $108.0

Per tree damage

IslandMedium annual

damages/K

Kauai $9.74

Oahu $11.30

Maui $8.93

Hawaii $2.88

Molokai $22.09

Cost of control?

IslandSearch Constant

($1000*acre)Search Coefficient

()Treatment Coefficient

Kauai $158,490,570 1.6095

$13.39

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( , ) 13.39 *c n x x

n

Current population?

0nIsland

Kauai 1,540

Oahu 6,890

Maui 111,050

Hawaii 315,000

Molokai 0

Optimal population

0n *nIsland

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 nothingRemain at

current population forever

Status quo spending

Optimal policyof 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

RegionAverage

PriceFrogs500m

Frogs800m

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

TransactionsFrogs within 800 m

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 50,033 50,033

Adj R2 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!