Previous research shows that firms shroud high add-on prices in competitive markets with naive consumers leading to inefficiency. We analyze the effects of regulatory intervention via educating naive consumers on equilibrium prices and welfare. Our model allows firms to shroud, unshroud, or...

We model a boundedly rational agent who suffers from limited attention. The agent considers each feasible alternative with a given (unobservable) probability, the attention parameter, and then chooses the alternative that maximises a preference relation within the set of considered alternatives....

We propose an extension of Tversky's lexicographic semiorder to a model of boundedly rational choice. We explore the connection with sequential rationalisability of choice, and we provide axiomatic characterisations of both models in terms of observable choice data.

In this paper we question the hypothesis of full rationality in the context of job changing behavior, via simple econometric explorations on microdata drawn from WHIP (Worker Histories Italian Panel). A rational outcome of the job matching process implies a positive tradeoff between future wages...

Economists traditionally tackle normative problems by computing optimal policy, i.e. the one that maximizes a social welfare function. In practice, however, a succession of marginal changes to a limited number of policy instruments are implemented, until no further improvement is feasible. I...

We study and test a class of boundedly rational models of decision making which rely on sequential eliminative heuristics. We formalize two sequential decision procedures, both inspired by plausible models popular among several psychologists and marketing scientists. However we follow a standard...

In this paper we question the hypothesis of full rationality in the context of job changing behaviour, via simple econometric explorations on microdata drawn from WHIP (Worker Histories Italian Panel). Workers’ performance is compared at the end of a three-year time window that starts when...