An economically-consistent discrete choice model with flexible utility specification based on artificial neural networks

arXiv:2404.13198v1 Announce Type: cross
Abstract: Random utility maximisation (RUM) models are one of the cornerstones of discrete choice modelling. However, specifying the utility function of RUM models is not straightforward and has a considerable impact on the resulting interpretable outcomes and welfare measures. In this paper, we propose a new discrete choice model based on artificial neural networks (ANNs) named "Alternative-Specific and Shared weights Neural Network (ASS-NN)", which provides a further balance between flexible utility approximation from the data and …

abstract artificial artificial neural networks arxiv consistent cs.lg econ.em function however impact modelling networks neural networks paper random stat.ml type utility welfare