Abstract
Choice experiments addressing outcome uncertainty (OU) typically reframe continuous probability densities for each risky outcome into two discrete categories, each with a single probability of occurrence. The implications of this simplification for welfare estimation are unknown. This article evaluates the convergent validity of willingness-to-pay (WTP) estimates from a more accurate multiple-outcome treatment of OU, compared to the two-outcome approach. Results for a case study of coastal flood adaptation in Connecticut, United States, suggest that higher-resolution OU treatments increase choice complexity but can provide additional information on risk preferences and WTP. This tradeoff highlights challenges facing the valuation of uncertain outcomes.
Highlights
Choice experiments addressing outcome uncertainty (OU) typically reframe continuous probability densities for each risky outcome into two discrete categories, each with a single probability of occurrence
Discrete choice experiments (DCEs) in environmental economics often include choice attributes that are subject to outcome uncertainty (OU), defined as uncertainty about whether attribute levels indicated in valuation scenarios will occur when policies are implemented
To evaluate these dual concerns, we develop a coupled theoretical and empirical model for a case study of coastal climate change adaptation in the town of Old Saybrook, Connecticut, United States
Summary
Choice experiments addressing outcome uncertainty (OU) typically reframe continuous probability densities for each risky outcome into two discrete categories, each with a single probability of occurrence. Results for a case study of coastal flood adaptation in Connecticut, United States, suggest that higher-resolution OU treatments increase choice complexity but can provide additional information on risk preferences and WTP This tradeoff highlights challenges facing the valuation of uncertain outcomes. Most DCEs include no formal communication of OU (Lundhede et al 2015) Underlying this treatment is an often-unstated assumption that outcomes are certain (Wielgus et al 2009, Glenk and Colombo 2013) or that individuals’ utilities depend only on attributes’ final states (Roberts, Boyer, and Lusk 2008). Most DCEs that address OU in this way allow for only two possible outcomes of each risk-related attribute, with each outcome distinguished by an exogenously varying numerical probability embedded within the choice set We refer to this as a binary treatment of OU. This practice is common both for studies addressing the success of policy interventions and those estimating the value of risk reductions
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