Many prominent regularities of stochastic choice, such as the attraction, similarity and compromise effects, are incompatible with Random Utility Maximisation (RUM) as they violate Monotonicity. We argue that these regularities can be conveniently represented by a variation of RUM in which utility depends on only two states and state probabilities are allowed to depend on the menu. We call this model Dual Random Utility Maximisation (dRUM). dRUM is a parsimonious model that admits violations of Monotonicity. We characterise dRUM in terms of three transparent expansion/contraction conditions. We also characterise the important special case in which state probabilities are constant across menus.</p
Chapter 1 introduces and axiomatizes a new class of representations for incomplete preferences calle...
We generalize the stochastic revealed preference methodology of McFadden and Richter (1990) for fini...
Suppose that, when evaluating two alternatives x and y by means of a parametric utility function, lo...
Dual Random Utility Maximisation (dRUM) is Random Utility Maximisation when utility depends on only ...
We propose a novel model of stochastic choice: the single-crossing random utility model (SCRUM). Thi...
The (static) utility maximization model of Afriat (1967), which is the standard in analysing choice ...
We study stochastic choice as the outcome of deliberate randomization. We derive a general represent...
We study stochastic choice as the outcome of deliberate randomization. We derive a general represent...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Chapter 1 introduces and axiomatizes a new class of representations for incomplete preferences calle...
We generalize the stochastic revealed preference methodology of McFadden and Richter (1990) for fini...
Suppose that, when evaluating two alternatives x and y by means of a parametric utility function, lo...
Dual Random Utility Maximisation (dRUM) is Random Utility Maximisation when utility depends on only ...
We propose a novel model of stochastic choice: the single-crossing random utility model (SCRUM). Thi...
The (static) utility maximization model of Afriat (1967), which is the standard in analysing choice ...
We study stochastic choice as the outcome of deliberate randomization. We derive a general represent...
We study stochastic choice as the outcome of deliberate randomization. We derive a general represent...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Discrete choice models are usually derived from the assumption of random utility maximization. We co...
Chapter 1 introduces and axiomatizes a new class of representations for incomplete preferences calle...
We generalize the stochastic revealed preference methodology of McFadden and Richter (1990) for fini...
Suppose that, when evaluating two alternatives x and y by means of a parametric utility function, lo...