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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 xn 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!