Stochastic Monotonicity and Random Utility Models: The Good and The Ugly

TL;DR

This paper revisits the validity of random utility models in economic choice analysis, proposing a relaxed monotonicity framework and introducing new models that align with empirical data and existing applications.

Contribution

It introduces a new class of random utility models with relaxed monotonicity conditions, reconciling some criticisms and showing existing models fit within this framework.

Findings

Some random utility models satisfy relaxed monotonicity criteria.

Existing models like the certainty-equivalent-based RUM for CARA utility are compatible.

The critique of all RUMs being invalid is overly broad.

Abstract

When it comes to structural estimation of risk preferences from data on choices, random utility models have long been one of the standard research tools in economics. A recent literature has challenged these models, pointing out some concerning monotonicity and, thus, identification problems. In this paper, we take a second look and point out that some of the criticism - while extremely valid - may have gone too far, demanding monotonicity of choice probabilities in decisions where it is not so clear whether it should be imposed. We introduce a new class of random utility models based on carefully constructed generalized risk premia which always satisfy our relaxed monotonicity criteria. Moreover, we show that some of the models used in applied research like the certainty-equivalent-based random utility model for CARA utility actually lie in this class of monotonic stochastic choice models. We conclude that not all random utility models are bad.