Cost vector effects in forced-choice discrete choice experiments: Assessing the acceptability of future glyphosate policies

Abstract

One way to evaluate future policies that significantly deviate from the status quo is through discrete choice experiments (DCEs) with a reference policy featuring a positive cost and no opt-out option. This study examines how the design of the cost vector, particularly the cost assigned to the reference policy, influences DCE outcomes in this context. Focusing on glyphosate phase-out policies in France, we compare a strict ban (used as the reference policy) with taxation alternatives. Using a split-sample design with two groups of 500 individuals, we analyze how variations in the ban’s cost and the associated cost range affect welfare estimates. Our findings reveal that while overall preference rankings remain consistent across samples, willingness-to-pay for some attributes increases when the reference policy’s cost rises. We explore potential drivers of this effect, including the inability to choke off demand for the ban, strategic biases, attribute non-attendance, relative evaluation, and anchoring bias. The results suggest that relative evaluation and anchoring bias are the most likely explanations for the observed differences. These findings provide methodological insights for addressing cost vector effects in DCEs. • Split-sample to study the effect of the cost vector design in discrete choice experiments with no opt-out option. • We use a future policy that deviates significantly from the status quo as the reference. • The reference cost influences respondents through anchoring bias and relative evaluation. • Heavy taxation seems an acceptable alternative to a strict ban to phase-out glyphosate. • We point-out the importance of accurately estimating policy costs before DCE valuation and conducting sensitivity analysis.