The purpose of this meta-analysis was to estimate the benefits associated with water quality improvements in US water bodies and to determine if benefit transfer errors can be reduced with the introduction of geospatial information to the meta-regression. Economic theory predicts that welfare estimates should be influenced by geospatial information regarding resource scale, market extent, and availability of substitutes and complements.
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A total of 140 observations from 51 primary studies were gathered from the stated preference literature on water quality improvements. Using the estimated valuation meta-function, household willingness-to-pay (WTP) was estimated for an 18-point improvement on the 100-point Water Quality Index (WQI) from a baseline of 36. The WTP estimates ranged from USD 17 to USD 434 (2007 US Dollars), depending on the specification of geospatial variables in the meta-function. Convergent validity tests revealed that transfer errors increased by 5-6% when geospatial variables were omitted. Results of this study suggest that, where possible, future benefit transfers should account for geospatial factors such as resource scale, market extent, and availability of substitutes when estimating welfare measures for policy sites.
Five scenarios were created to demonstrate the sensitivity of the estimated Willingness to Pay (WTP) values to changes in the geospatial variables. For each scenario, household WTP for a water quality improvement equal to 18.3 points on the 100-point WQI scale (from a baseline of 36.2) was estimated using each of the three model specifications. Household WTP ranged from USD 17.12 to USD 433.58 (2007 USD), depending on what the geospatial variables were set at in the meta-function.
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