We present a demonstration of a Bayesian spatial probit model for adichotomous choice contingent valuation method willingness-to-pay (WTP)questions. If voting behavior is spatially correlated, spatialinterdependence exists within the data, and standard probit models willresult in biased and inconsistent estimated nonbid coefficients. Adjustingsample WTP to population WTP requires unbiased estimates of the nonbidcoefficients, and we find a $17 difference in population WTP per householdin a standard vs. spatial model. We conclude that failure to correctly modelspatial dependence can lead to differences in WTP estimates with potentiallyimportant policy ramifications.
