Dispersion-induced status quo bias in pivot-designed choice experiment

Two drivers of the status quo bias are explored via a split sample survey with a pivot-designed Discrete Choice Experiment interviewing recreational fishers in Italy. The propensity to favor the status quo over the hypothetical alternatives given an individual reference point, which we call “dispersion” is examined and modelled accordingly. The framing of the status quo alternative, as a driver of bias, is explored as reference point or opt-out option. Our findings demonstrate that when the status quo is characterized as an individual-specific reference, the status quo bias increases with the magnitude of the dispersion, leading to potentially biased willingness-to-pay estimates. Conversely, when the status quo is characterized as an opt-out option, the effect of the dispersion diminishes, improving the robustness of the estimates. Our results underscore the importance of carefully designing choice scenarios to manage status quo bias. In order to improve the accuracy of welfare estimates, a novel random utility model that tests and accounts for the effects of dispersion is proposed. The performance of this model is numerically tested in a series of Monte Carlo experiments.