Correlated Choice

TL;DR

This paper investigates the structure of random joint choice rules with interdependent choices, characterizing when such rules can be considered separable, and identifying conditions for their equivalence.

Contribution

It provides two characterizations of separable random joint choice rules and introduces an additional condition that, combined with marginality, ensures separability.

Findings

Marginality is necessary but not sufficient for separability.

Two characterizations of separable choice rules are provided.

An extra condition on marginal choice rules guarantees separability.

Abstract

We study random joint choice rules, allowing for interdependence of choice across agents. These capture random choice by multiple agents, or a single agent across goods or time periods. Our interest is in separable choice rules, where each agent can be thought of as acting independently of the other. A random joint choice rule satisfies marginality if for every individual choice set, we can determine the individual's choice probabilities over alternatives independently of the other individual's choice set. We offer two characterizations of random joint choice rules satisfying marginality in terms of separable choice rules. While marginality is a necessary condition for separability, we show that it fails to be sufficient. We provide an additional condition on the marginal choice rules which, along with marginality, is sufficient for separability.