Capturing More Relevant Measures of Spatial Heterogeneity in Stated Preference Willingness to Pay: Using an Iterative Grid Search Algorithm to Quantify Proximate Environmental Impacts

Willingness to pay (WTP) for public goods is often spatially heterogeneous; the relevance of thisheterogeneity for policy analysis is increasingly recognized. Within stated preference (SP) analysis,the most commonly analyzed form of spatial heterogeneity is distance decay, in which WTPis assumed to diminish as a monotonic function of distance from the affected resource. This distanceis typically calculated from each respondent’s household to the nearest point of the affectedresource, using either Euclidean or travel distance. A small but increasing literature, however, nowsuggests the limitations of a simple distance decay paradigm as the sole means to evaluate spatialheterogeneity. This article illustrates a novel approach to account for spatial welfare heterogeneitythat may better capture the systematic sensitivity of preferences to resource proximity. The modelaccounts for the amount of the affected resource surrounding each respondent’s home location,at distance bands of varying length, rather than the distance to the closest point. This alternative“quantity-within-distance-x” measure is used as a substitute for the common “distance-to-nearestpoint”measure with distance-related models of spatial welfare heterogeneity. Methods and resultsare illustrated using a choice experiment addressing preferences for riparian land restoration insouth coastal Maine. Results suggest that the resulting models better capture spatial elementsrelevant to respondents’ preferences. Comparison to standard distance decay models shows theadditional insight provided by this novel approach.