  The random utility model (RUM, McFadden and Richter, 1990) has been the
standard tool to describe the behavior of a population of decision makers. RUM
assumes that decision makers behave as if they maximize a rational preference
over a choice set. This assumption may fail when consideration of all
alternatives is costly. We provide a theoretical and statistical framework that
unifies well-known models of random (limited) consideration and generalizes
them to allow for preference heterogeneity. We apply this methodology in a
novel stochastic choice dataset that we collected in a large-scale online
experiment. Our dataset is unique since it exhibits both choice set and
(attention) frame variation. We run a statistical survival race between
competing models of random consideration and RUM. We find that RUM cannot
explain the population behavior. In contrast, we cannot reject the hypothesis
that decision makers behave according to the logit attention model (Brade and
Rehbeck, 2016).
