Can you ever be certain? Reducing hypothetical bias in stated choice experiments via respondent reported choice certainty

• The hypothetical nature of stated preference experiments can create biased results.
• Mitigation is attempted by calibrating models based on the certainty of choice being made.
• Unique stated and revealed preference experiment is used to assess mitigation.
• Incorrect use of certainty calibration can induce greater levels of bias.
• Jointly estimating choice and choice certainty significantly reduces hypothetical bias.

Stated choice experiments are a preeminent method for researchers and practitioners who seek to examine the behavior of consumers. However, the extent to which these experiments can replicate real markets continues to be debated in the literature, with particular reference to the potential for biased estimates as a result of the hypothetical nature of such experiments. In this paper, a first in the transportation literature, we compare stated choice responses to revealed preference behavior and examine three methods proposed in the literature for calibrating choice experiments via reported choice certainty. In doing so we provide evidence that the incorrect calibration of responses can produce stated choice results that are more biased than doing nothing at all, however we show that by jointly estimating choice and choice certainty there is a significant reduction in hypothetical bias such that stated choice responses more directly replicate real behavior.