Reference Dependence and Random Attention

TL;DR

This paper introduces the Reference-Dependent Random Attention Model (RD-RAM), which explains how reference points influence attention and choice behavior, capturing complex patterns like reversals and overloads within a stochastic choice framework.

Contribution

It provides a behavioral foundation for RD-RAM, characterizes conditions for preference identification, and extends models of stochastic consideration to include reference dependence.

Findings

Preferences are identifiable despite reference-dependent attention.

RD-RAM captures frequency reversals and choice overload.

Characterizes reference-dependent versions of prominent stochastic consideration models.

Abstract

We explore the ways that a reference point may direct attention. Utilizing a stochastic choice framework, we provide behavioral foundations for the Reference-Dependent Random Attention Model (RD-RAM). Our characterization result shows that preferences may be uniquely identified even when the attention process depends arbitrarily on both the menu and the reference point. The RD-RAM is able to capture rich behavioral patterns, including frequency reversals among non-status quo alternatives and choice overload. We also analyze specific attention processes, characterizing reference-dependent versions of several prominent models of stochastic consideration.