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

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.