Addressing Negative Willingness to Pay in Dichotomous Choice Contingent Valuation

This paper has four purposes. First, we outline the controversy surroundingthe issue of negative willingness to pay (WTP)in contingent valuation (CV) studies. Second,we use Monte Carlo simulation to examine theperformance of alternative distributionalassumptions in estimating WTP in the presenceof varying proportions of the populationholding negative WTP values. We focus ondichotomous choice CV (DC-CV), where negativeWTP values may be especially difficult todetect. Third, we extend the simulation toinvestigate the performance of the mixturemodels that have recently been proposed forhandling/identifying non-positive WTP values. Fourth, we extend the simulation to investigatethe performance of the nonparametric lowerbound Turnbull approach. Results indicate thatthe relative performance of the DC-CV modelingalternatives evaluated here, which assumepositive WTP, varies across the simulationsetting (e.g., proportion of negative WTP); butnone can be said to reasonably ``solve' theproblem ex post. This underscores theimportance of ex ante efforts to identify ifnegative WTP is likely to be prominent in agiven valuation setting. In such cases,appropriately handling negative WTP must beaddressed through ex ante survey design andmodeling choices that allow negative WTP.