Economics
Enhanced Geospatial Validity for Meta-analysis and Environmental Benefit Transfer: An Application to Water Quality Improvements
Document Type
Article
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.
Publication Title
Environmental and Resource Economics
Publication Date
10-2017
Volume
68
Issue
2
First Page
343
Last Page
375
ISSN
0924-6460
DOI
10.1007/s10640-016-0021-7
Keywords
benefit function transfer, ecosystem service, meta-analysis, non-market valuation, nonuse value, spatial, willingness to pay
Repository Citation
Johnston, Robert J.; Besedin, Elena Y.; and Stapler, Ryan, "Enhanced Geospatial Validity for Meta-analysis and Environmental Benefit Transfer: An Application to Water Quality Improvements" (2017). Economics. 163.
https://commons.clarku.edu/faculty_economics/163

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