The (static) utility maximization model of Afriat (1967), which is the standard in analysing choice behavior, is under scrutiny. We propose the Dynamic Random Utility Model (DRUM) that is more flexible than the framework of Afriat (1967) and more informative than the static Random Utility Model (RUM) framework of McFadden and Richter (1990). Under DRUM, each decision-maker randomly draws a utility function in each period and maximizes it subject to a menu. DRUM allows for unrestricted time correlation and cross-section heterogeneity in preferences. We characterize DRUM for situations when panel data on choices and menus are available. DRUM is linked to a finite mixture of deterministic behaviors that can be represented as a product of stati...
Dual Random Utility Maximisation (dRUM) is Random Utility Maximisation when utility depends on only ...
In a comment to Cappelen, Hole, Sørensen, and Tungodden (2007b), Conte and Moffatt (2009) challenge ...
We generalize the stochastic revealed preference methodology of McFadden and Richter (1990) for fini...
We provide an axiomatic analysis of dynamic random utility, characterizing the stochastic choice beh...
We provide an axiomatic analysis of dynamic random utility, characterizing the stochastic choice beh...
I study dynamic random utility with finite choice sets and exogenous total menu variation, which I r...
Under dynamic random utility, an agent (or population of agents) solves a dynamic decision problem s...
The Random Utility Model (RUM) and the Random Preference Model (RPM) are important tools in the econ...
Under dynamic random utility, an agent (or population of agents) solves a dynamic decision problem s...
While the paradigm of utility maximisation has formed the basis of the majority of applications in d...
The random utility model (RUM, McFadden and Richter, 1990) has been the standard tool to describe th...
Many prominent regularities of stochastic choice, such as the attraction, similarity and compromise ...
Applied studies of commercial fishing have largely ignored the intertemporal aspects of repeated sit...
In a comment to Cappelen, Hole, Sørensen, and Tungodden (2007b), Conte and Moffatt (2009) challenge...
In a comment to Cappelen, Hole, Sørensen, and Tungodden (2007b), Conte and Moffatt (2009) challenge...
Dual Random Utility Maximisation (dRUM) is Random Utility Maximisation when utility depends on only ...
In a comment to Cappelen, Hole, Sørensen, and Tungodden (2007b), Conte and Moffatt (2009) challenge ...
We generalize the stochastic revealed preference methodology of McFadden and Richter (1990) for fini...
We provide an axiomatic analysis of dynamic random utility, characterizing the stochastic choice beh...
We provide an axiomatic analysis of dynamic random utility, characterizing the stochastic choice beh...
I study dynamic random utility with finite choice sets and exogenous total menu variation, which I r...
Under dynamic random utility, an agent (or population of agents) solves a dynamic decision problem s...
The Random Utility Model (RUM) and the Random Preference Model (RPM) are important tools in the econ...
Under dynamic random utility, an agent (or population of agents) solves a dynamic decision problem s...
While the paradigm of utility maximisation has formed the basis of the majority of applications in d...
The random utility model (RUM, McFadden and Richter, 1990) has been the standard tool to describe th...
Many prominent regularities of stochastic choice, such as the attraction, similarity and compromise ...
Applied studies of commercial fishing have largely ignored the intertemporal aspects of repeated sit...
In a comment to Cappelen, Hole, Sørensen, and Tungodden (2007b), Conte and Moffatt (2009) challenge...
In a comment to Cappelen, Hole, Sørensen, and Tungodden (2007b), Conte and Moffatt (2009) challenge...
Dual Random Utility Maximisation (dRUM) is Random Utility Maximisation when utility depends on only ...
In a comment to Cappelen, Hole, Sørensen, and Tungodden (2007b), Conte and Moffatt (2009) challenge ...
We generalize the stochastic revealed preference methodology of McFadden and Richter (1990) for fini...