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

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.

A Global Meta-Analysis of the Value of Ecosystem Services Provided by Lakes

“…Johnston et al (2016) provide a recent example of this type of “augmented” meta-analysis for the case of water quality in the United States. Our choice of additional spatial variables has been primary guided by economic theory (which predicts which factors are supposed to influence willingness to pay) and by data availability at the global scale.…”

Mapping Ecosystem Services for Marine Planning: A UK Case Study

“…The novelty of this work lies in its application (marine environment) and the tool's ability to use both primary (biophysical) and secondary data (economic) to produce spatially-specific economic estimates for short-term spatial planning to local decision-makers and stakeholders. The emphasis on the short term is due to all types of values changing through time, with economic estimates needing to be discounted and be geographically adjusted and specific [54,55], if different or more targeted estimates become available. As long as suitable high-quality data are available from primary collection (e.g., for economic data) or from rigorous monitoring or survey practices (e.g., for biochemical data), mapping of ecosystem services and their value can be enhanced through the use of GIS, serving as a stepping stone for Natural Capital accounts for specific ecosystem services flows and assets in the marine and coastal environment.…”

Valuing non-market economic impacts from natural hazards

“…For example, Smith and Huang (1993) review the use of hedonic pricing models to assess values for air pollution reductions over more than a 25-year span. The volume of valuation work is demonstrated in meta-analysis studies associated with topics such as reductions in pesticide risk exposure (Florax et al 2005); mortality risk reductions (Lindhjem et al 2011); improvements in water quality (Johnston et al 2005(Johnston et al , 2017a(Johnston et al , 2018aVan Houtven et al 2007;Johnston and Thomassin 2010;Newbold et al 2018); as well as meta-analyses of values for recreation (e.g. Zandersen and Tol 2009); forests (e.g.…”