Strategic response to a sequence of discrete choice questions

Abstract

According to neoclassical economic theory, the only stated preference elicitation format that can feasibly be employed in field studies to which truthful response can be the dominant strategy for all respondents is a single binary choice between the status quo and one alternative. In studies where the objective is estimation of preferences for multiple attributes of a good, it is preferred (and, in some cases, necessary) based on econometric considerations, to present respondents with a sequence of choice tasks. Economic theory predicts that utility-maximising respondents may find it optimal to misrepresent their preferences in this elicitation format. In this paper, the effect on stated preferences of expanding the number of choice tasks per respondent from one to four is tested using a split sample treatment in an attribute-based survey relating to the undergrounding of overhead electricity and telecommunications wires in the Australian Capital Territory. We find evidence to suggest that presenting multiple choice tasks per respondent decreases estimates of total willingness to pay and that this effect is related to the ordering of cost levels presented over the sequence of choice tasks. Two behavioural explanations can be advanced - a weak cost minimisation strategy, which implies divergence between stated and true preferences, and a ‘good deal / bad deal’ heuristic, in which stated preferences reflect true preferences that change over the course of the sequence of choice tasks. Preferences stated in the first of a sequence of choice tasks are not significantly different from those stated in the incentive compatible single binary choice task. A key objective of future research will be to establish whether this effect becomes less prevalent as the number of attributes and alternatives per choice task are increased.Choice experiments, willingness to pay, incentive compatibility, strategic behaviour, order effects, underground electricity, Research Methods/ Statistical Methods,