Modeling Distance Decay Within Valuation Meta-Analysis

Abstract

Environmental benefit transfers increasingly rely on welfare estimates generated using meta-regression models (MRMs) of non-market willingness to pay (WTP). Theory and intuition suggest that these estimates should generally be sensitive to spatial dimensions. A common spatial pattern found in primary valuation studies is distance decay, in which WTP for environmental improvements diminishes as a function of distance to affected areas. Despite the potential importance of distance decay for benefit transfer accuracy, no valuation MRM in the published literature has developed an explicit mechanism to account for it. This paper outlines an approach to model the systematic effect of distance within valuation MRMs. The approach is illustrated using a meta-analysis of WTP for quality improvements in US water bodies. The metadata are drawn from stated preference studies that estimate per household WTP for water quality changes, and combine primary study information with external geospatial data. Results demonstrate statistically significant and intuitive influences of distance and other spatial factors on WTP. The resulting benefit transfers are more accurate than otherwise identical transfers that cannot account for spatial variations.