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Natural Resource Damage Assessment: Methods and Cases

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household were not significant predictors of willingness to pay.<br />

Poe (1998) examined willingness of private well owners to pay for a groundwater<br />

protection program that would ensure that nitrate st<strong>and</strong>ards remain below 10mg/L in Portage<br />

County, Wisconsin. Willingness to pay was found to be significantly positively related to<br />

existing nitrate levels in the well, <strong>and</strong> either age, education, or income.<br />

Poe <strong>and</strong> Bishop (1999) estimated willingness to pay for a groundwater protection<br />

program that would reduce nitrate levels in all Portage County wells by 25%. They found that<br />

willingness to pay increased with nitrate concentrations, but the rate of increase was diminishing<br />

with contamination levels. They also found that nonuse concerns for the health of others had a<br />

positive significant effect on willingness to pay. Actual averting actions that have been<br />

undertaken did not negatively impact willingness to pay. The estimated willingness to pay for a<br />

25% reduction from 14.5 mg/L was $412 per year per household. This study was based on a<br />

well-developed theoretical model of willingness to pay <strong>and</strong> the researchers provided respondents<br />

with information on the nitrate levels in the researchers’ own well.<br />

Crutchfield et al. (1997) examined the willingness to pay for installation of a water filter<br />

that could either reduce nitrates in tap water to safer levels or completely eliminate nitrates from<br />

drinking water to households in the White River Region in Indiana, Central Nebraska, Lower<br />

Susquehanna <strong>and</strong> Mid-Columbia Basin in Washington State. They found that willingness to pay<br />

was positively related to income, extra income, <strong>and</strong> number of years lived in the zip code, but<br />

negatively related to age. The higher estimate obtained by Crutchfield et al. (1997) as compared<br />

to that obtained by Poe <strong>and</strong> Bishop (1999) could reflect the incremental benefits of reducing<br />

nitrates from safe levels to zero.<br />

Hurley et al. (1999) used data from a CV study in Clark <strong>and</strong> Adams counties in Iowa to<br />

determine rural residents’ willingness to pay to delay nitrate contamination of their water supply<br />

from large animal confinement facilities by 10, 15, <strong>and</strong> 20 years. Both counties relied heavily on<br />

surface water supplies for drinking water. The researchers found that higher education, income<br />

<strong>and</strong> expected length of time to remain in the community were positively <strong>and</strong> significantly related<br />

with willingness to pay values. Willingness to pay ranged from $118/HH/year for a 10 year delay<br />

to $191/HH/year for a 20 year delay by a household with sample mean characteristics. However,<br />

the study suffered from a low overall response rate, a small sample of private well users that<br />

would be affected by nitrate contamination, <strong>and</strong> the fact that over 50% of the survey respondents<br />

rejected the scenario <strong>and</strong> stated no willingness to pay for any delay in nitrate contamination.<br />

Benefit transfer methods are one way to use these estimated values for policy analysis or<br />

for inferring the value of groundwater in other regions. Crutchfield et al. (1995) used benefits<br />

transfer methods using the three previous studies summarized in Table 3.3 (Shultz <strong>and</strong> Lindsay,<br />

1990; Jordan <strong>and</strong> Elnagheeb, 1993; <strong>and</strong> Sun et al., 1992) together with farm <strong>and</strong> county level<br />

data for four regions (the White River Region in Indiana, Central Nebraska, the Lower<br />

Susquehanna River, <strong>and</strong> the Mid-Columbia Basin in Washington State) <strong>and</strong> estimated the<br />

benefits of protecting rural drinking water from contamination caused by agricultural chemical<br />

residues. They use the data collected from the four regions being studied to substitute for the<br />

explanatory variables used in the three original studies <strong>and</strong> estimated willingness to pay for those<br />

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