Translating invasive species science into policy Kimberly Burnett, University of Hawaii

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, HI All Miconia photo credits: K. Burnett, near Hana

How fast does it grow? IslandK Kauai15,849,057 Oahu8,713,551 Maui14,133,791 Hawaii78,216,124 Molokai3,087,479 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) Total annual damages by island (millions) Island # birdsLowHighLowMediumHigh Kauai $91.6$154.0$234.0 Oahu $61.4$98.5$145.0 Maui $77.8$126.0$187.0 Big Island $169.0$225.0$297.0 Molokai 11N/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? Island Search Constant ($1000*acre) Search Coefficient (  ) Treatment Coefficient Kauai$158,490, $13.39 Oahu$87,135, Maui$141,337, Big Island$782,161, Molokai$30,874,7901.6

Current population? Island Kauai1,540 Oahu6,890 Maui111,050 Hawaii315,000 Molokai0

Optimal population Island Kauai1,5409,171 Oahu6,8905,495 Maui111,0508,901 Hawaii315,00039,937 Molokai00

Policy comparisons IslandPolicy 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, 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, 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 AcresN. Obs. Puna$26, %34.1%2.624,019 S Hilo$126,1415.7%23.2%10.84,443 N Hilo$283,3837.0% Hamakua$154, %25.5% N Kohala$202, %42.9%10.41,758 S Kohala$409, %48.4%6.83,479 N Kona$334, %33.9%2.96,733 S Kona$773, %40.6%21.72,064 Kau$25, %23.8%8.75,981

Puna Close-up Frogs within 500 m Transactions Frogs within 800 m

Impact on Property Price VariableFrogs 500mFrogs 800m Frogs-135,957*** (19327) -6,816 (7845) SFLA 67*** (4) 64*** (4) Assessed Land Val 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 observations50,033 Adj R ***,** 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!