Enhanced Geospatial Validity for Meta-analysis and Environmental Benefit Transfer: An Application to Water Quality Improvements

Robert Johnston, Elena Y. Besedin () and Ryan Stapler ()
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Elena Y. Besedin: Abt Associates Inc.
Ryan Stapler: Athenahealth

Environmental & Resource Economics, 2017, vol. 68, issue 2, No 6, 343-375

Abstract: Abstract Meta-regression models are commonly used within benefit transfer to estimate willingness to pay (WTP) for environmental quality improvements. Theory suggests that these estimates should be sensitive to geospatial factors including resource scale, market extent, and the availability of substitutes and complements. Valuation meta-regression models addressing the quantity of non-market commodities sometimes incorporate spatial variables that proxy for a subset of these effects. However, meta-analyses of WTP for environmental quality generally omit geospatial factors such as these, leading to benefit transfers that are invariant to these factors. This paper reports on a meta-regression model for water quality benefit transfer that incorporates spatially explicit factors predicted by theory to influence WTP. The metadata are drawn from stated preference studies that estimate per household WTP for water quality changes in United States water bodies, and combine primary study information with extensive geospatial data from external sources. Results find that geospatial variables are associated with significant WTP variations as predicted by theory, and that inclusion of these variables reduces transfer errors.

Keywords: Non-market valuation; Benefit function transfer; Meta-analysis; Spatial; Willingness to pay; Nonuse value; Ecosystem service (search for similar items in EconPapers)
JEL-codes: Q25 Q51 Q53 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (25)

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DOI: 10.1007/s10640-016-0021-7

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