Linking Forests to Faucets with a Distant Municipal Area: Investigating Public Support for Water Security and Watershed Protection Dadhi Adhikari Janie Chermak Jennifer Thacher Robert P. Berrens

Study Area

Survey Approach Two Focus Groups & 100 pre-test surveys Population: 190,000 Albuquerque households, obtained from County Assessor Data provided by ABCWUA Sampling frame: 104,000 home owners Sample selected: 2596, proportional to HH# by zipcodes Five contacts (two mailed questionnaires 9/ /2013 Responses received through mail and internet Mailed surveys: 2596 Undelivered surveys: 133 Net mailed surveys: 2463 Responses (n=911): (a) Mail-751 (b) Online-160 Response Rate: 37%

Willingness to Pay Study Good to be Valued : Creating water source protection fund to conduct land treatments on 30,000 acres/yr in watershed lands north of Albuquerque to reduce the risk of high-severity wildfire. Payment Vehicle : Annual fee collected through water utility bills, property taxes, or insurance premium taxes. Valuation Question: Currently overgrown brush and trees are removed from approximately 3000 acres/year in the larger watershed. The University of New Mexico is trying to figure out at what level, if any, metropolitan Albuquerque homeowners would support a Water Source Protection Fund to conduct land treatments on 30,000 acres/year in the same area and reduce the risk of high- severity wildfire. A required annual fee of all homeowners could be targeted for this purpose. Different people might be willing to pay different amounts to the Water Protection Fund. What is the most your household would be willing to pay per year to the Water Source Protection Fund ? Fill in the blank $ per year

Uncertainty Delivery Uncertainty- Two questions ◦ On a scale of 0 to 10, where 0 means “Not at all likely” and 10 means “Highly likely” and 5 is halfway in between, how likely do you feel it is that wildfires will impact your supply of drinking water if fire-prone land in the watershed are not treated to reduce wildfire risk? Circle one. ◦ Suppose the Water Source Protection Fund is put in place and funds are targeted to minimize the risk of high-severity wildfire in the forested area north of Albuquerque. On a scale of 0 to 10, where 0 means “Not at all effective” and 10 means “Highly effective” and 5 is halfway in between, how effective do you feel the program would be in ensuring the sustainability of maintaining metropolitan Albuquerque’s supply of water ? Preference Uncertainty – After the WTP question ◦ On a scale of 0 to 10, where 0 means “Completely uncertain” and 10 means “Completely certain” and 5 is halfway in between, how certain are you of your answer to question 11 (wtp question)?

Descriptive Statistics VariableDescriptionObsMean (St.D) WTPWillingness to Pay ($/year) (81.86) PERCEPCCPerception on how serious the climate change problem is, measured in 1-4 likert scale (1- Not Serous, 4- Extremely serious) (1.03) PERCEPWSPerception on how serious the water supply problem is, measured in 1-4 likert scale (1- Not Serous, 4- Extremely serious) (0.80) PERCEPPWPerception on how serious the payment for water problem is, measured in 1-4 likert scale (1- Not Serous, 4- Extremely serious) (0.99) PERCEPWFRPerception on how serious the wildfire fire risk problem is, measured in 1-4 likert scale (1- Not Serous, 4- Extremely serious) (0.86) PERCEPTAXPerception on how serious the tax problem is, measured in 1-4 likert scale (1- Not Serous, 4- Extremely serious) (1.00) WHITE1 if white, 0 otherwise (0.37) MALE1 if male, 0 otherwise (0.49) FAMSIZEFamily Size (1.22) INCOMEIncome (measured in $1000) (44.11) EDU-UG1 if has undergraduate education, 0 otherwise (0.48) EDU-G1 if has graduate level education, 0 otherwise (0.48) YEARNMNumbers of years lived in the New Mexico (0.48) OPNPRCBRN1 if the respondent supports prescribed burning method of treating forest, 0 otherwise (0.44) DELIVUNCRNDelivery uncertainty measured in 0-10 likert scale, 0 being fully certain and 10 being fully uncertain (1.70)

WTP Distribution

Regression Results OLS W/O Uncertainty OLS With Uncertainty TOBIT W/O Uncertainty TOBIT (2) With Uncertainty Double Hurdle W/O Uncertainty Double Hurdle With Uncertainty PERCEPCC0.142** ** (2.21)(0.71)(2.10)(0.49)(0.74)(-0.02) PERCEPWS0.346***0.179**0.413***0.184*0.166**0.191** (3.73)(2.12)(3.93)(1.78)(2.50)(2.53) PERCEPPW-0.209***-0.207***-0.238***-0.223***-0.124**-0.171*** (-2.79)(-2.98)(-2.70)(-2.62)(-2.34)(-2.90) PERCEPWFR0.395***0.208**0.458***0.222**0.216***0.120* (4.47)(2.49)(4.61)(2.24)(3.50)(1.66) PERCEPTAX-0.363***-0.282***-0.416***-0.326***-0.193***-0.195*** (-4.67)(-3.81)(-4.71)(-3.81)(-3.64)(-3.30) WHITE * (0.60)(1.68)(0.52)(1.63)(0.66)(1.45) GENDER (0.73)(0.54)(0.73)(0.57)(0.28)(0.41) FAMSIZE (-0.45)(-0.71)(-0.37)(-0.54)(-0.93)(-0.90) INCOME *** *** *** *** * *** (3.11)(3.49)(2.77)(3.51)(1.88)(2.71) EDU-UG *0.297* (1.63)(1.46)(1.81)(1.65)(0.65)(0.21) EDU_G (0.50)(-0.02)(0.57)(0.07)(-0.37)(-0.96) YEARNM * ** * ** (-1.73)(-2.30)(-1.87)(-2.48)(-0.30)(-1.10) OPNPRCBRN0.410** *** ***0.178 (2.56)(1.08)(2.73)(1.19)(2.68)(1.46) DELIVUNCRN *** *** *** (-8.90) (-9.04) (-5.11) CONSTANT1.282**2.766*** ***2.962***3.304*** (2.44)(5.29)(1.31)(4.63)(8.26)(7.64) No.of Obs R-Square Log Likelihood AIC BIC

Mean and Median WTP ModelsMean WTP ($/year) Median WTP ($/year) OLS (without accounting for uncertainty) OLS (with accounting for uncertainty) Tobit (without accounting for uncertainty) Tobit (with accounting for uncertainty) Double Hurdle (without accounting for uncertainty) Double Hurdle (with accounting for ncertainty)

WTP: Albuquerque vs Santa Fe Mean Household WTP (Tobit Model) Without accounting for Uncertainty: approx $40/year With accounting for uncertainty: approx $31/year $/Month

Who should collect the funds?