In a discrete model, the predicted probabilities of a particular eventcan be matched to the observed (0, I) outcomes and this will give riseto a measure of fit for that event. Previous results for the binomialmodel are applied to multinomial models. In these models the measureof fit will vary...

We study a psychologically based foundation for choice errors. The decision maker applies a preference ranking after forming a 'consideration set' prior to choosing an alternative. Membership of the consideration set is determined both by the alternative specific salience and by the rationality...

We compare two options of integrating discrete working time choice of heterogenous households into a general equilibrium model. The first, known from the literature, produces household heterogeneity through a working time preference parameter. We contrast this with a model that directly...

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....

The paper discusses the nested logit model for choices between a set of mutually exclusive alternatives (e.g. brand choice, strategy decisions, modes of transportation, etc.). Due to the ability of the nested logit model to allow and account for similarities between pairs of alternatives, the...

This study models the choices of Dutch railway users (aggregated at the 4 digit post code area) for access mode and departure railway stations. For each post code area a set of four access modes: car, public transport, bicycle and walking and a set three departure railway stations are...

Within the context of the firm location choice problem, Guimara?es et al. (2003) have shown that a Poisson count regression and a conditional logit model yield identical coefficient estimates. Yet, the corresponding interpretation differs since these discrete choice models reflect polar cases as...

The multinomial logit model (MNL) is one of the most frequently used statistical models in marketing applications. It allows to relate an unordered categorical response variable, for example representing the choice of a brand, to a vector of covariates such as the price of the brand or variables...

Using daily Bundesbank foreign exchange market intervention data, we employ a multinomial logit approach to estimate an intervention reaction function for the German Central Bank using options implied volatilities and the deviation of the exchange rate from its target level as explanatory...