Stated choices and benefit estimates in the context of traffic calming schemes: Utility maximization, regret minimization, or both?

• We estimate a behavioural latent class comparing two choice paradigms (RR and RU).
• We explore the determinants of being best described by RR or RU choice behaviour.
• We derive adequate welfare estimates for this context of mixed choice behaviours.
• We associate familiarity with the choice context with utility maximization.
• Respondents unfamiliar with the choice context are likely to adopt regret minimization.

This paper proposes a discrete mixture model which assigns individuals, up to a probability, to either a class of random utility (RU) maximizers or a class of random regret (RR) minimizers, on the basis of their sequence of observed choices. Our proposed model advances the state of the art of RU–RR mixture models by (i) adding and simultaneously estimating a membership model which predicts the probability of belonging to a RU or RR class; (ii) adding a layer of random taste heterogeneity within each behavioural class; and (iii) deriving a welfare measure associated with the RU–RR mixture model and consistent with referendum-voting, which is the adequate mechanism of provision for such local public goods. The context of our empirical application is a stated choice experiment concerning traffic calming schemes. We find that the random parameter RU–RR mixture model not only outperforms its fixed coefficient counterpart in terms of fit—as expected—but also in terms of plausibility of membership determinants of behavioural class. In line with psychological theories of regret, we find that, compared to respondents who are familiar with the choice context (i.e. the traffic calming scheme), unfamiliar respondents are more likely to be regret minimizers than utility maximizers.