Cognitive Models of Bayesian Anchoring in Discrete Choice Experiments

Abstract

Discrete choice experiments are an important method to derive willingness-to-pay estimates for non-market goods. Several studies have shown that willingness-to-pay estimates derived from discrete choice experiments can be sensitive to the order of the presented choice tasks or the size of the presented costs, which raises concerns about the validity of such estimates. In this paper, we present cognitive models of Bayesian anchoring that control for choice-task ordering and cost-vector anomalies in discrete choice experiments. We show that ordering and cost-vector effects arise if respondents update their marginal utility of money based on the costs presented during the experiment and introduce novel models based on Bayesian updating that correct for anchoring processes at the individual level. Using data from a discrete choice experiment on micro- and nanoplastic pollution of freshwater ecosystems in Switzerland, we demonstrate how cognitive modeling can be used to correct willingness-to-pay estimates and discuss the implications for welfare analysis and policy design.

Keywords: environmental valuation, discrete choice experiments, anchoring, willingness-to-pay, Bayesian updating

JEL Classification: H41, H51, D61