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 this heterogeneity for policy analysis is increasingly recognized. Within stated preference (SP) analysis, the most commonly analyzed form of spatial heterogeneity is distance decay, in which WTP is assumed to diminish as a monotonic function of distance from the affected resource. This distance is typically calculated from each respondent’s household to the nearest point of the affected resource, using either Euclidean or travel distance. A small but increasing literature, however, now suggests the limitations of a simple distance decay paradigm as the sole means to evaluate spatial heterogeneity. This article illustrates a novel approach to account for spatial welfare heterogeneity that may better capture the systematic sensitivity of preferences to resource proximity. The model accounts 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 results are illustrated using a choice experiment addressing preferences for riparian land restoration in south coastal Maine. Results suggest that the resulting models better capture spatial elements relevant to respondents’ preferences. Comparison to standard distance decay models shows the additional insight provided by this novel approach.