The performance of full versus partial profile choice set designs in environmental valuation

An issue constantly raising concerns is the complexity of choice sets in stated choice experiments. Generally, designing choice sets requires trade-offs between the amount of information the researcher can derive, primarily through the number of attributes, and the measurement error caused by increased complexity. However, leaving specific attributes out might misrepresent the good in question and result in less information for decision-makers. An opportunity to reduce this trade-off is to apply partial profile designs. The basic idea is that not all attributes vary on all choice sets and that the overlap among attribute levels is controlled by the experimental design. Partial profile designs have rarely been used in environmental valuation, and if so, no split-sample approach was used to investigate performance differences. In this study, we aim to fill this gap by utilising both design types to value the good environmental status of the German North and Baltic Sea. We find that the partial profile design leads to significantly lower willingness-to-pay estimates, increased statistical efficiency as well as higher attribute attendance and less random choices. We thus recommend that researchers should consider partial profile designs more often as they promise clear benefits.