How to Segment a Search Market: Information Design and Directed Search

TL;DR

This paper analyzes how public information provision and market segmentation influence search efficiency and welfare in a two-sided market with vertically differentiated sellers, providing conditions for optimal segmentation design.

Contribution

It characterizes efficient and equilibrium buyer allocations in segmented search markets and derives conditions for optimal segmentation based on search externalities.

Findings

Equilibrium and socially efficient allocations are characterized.

A Hosios-type condition for efficiency is identified.

Optimal segmentation depends on search externalities.

Abstract

This paper examines when the public provision of information in search markets improves welfare. I consider a two-sided frictional search market in which buyers match with vertically differentiated sellers. The market is segmented into submarkets based on seller types. Such segmentation serves as a public signal that buyers use to direct their search. Given a segmentation, I characterize both the socially efficient and the equilibrium allocation of buyers across submarkets, and identify a Hosios-type condition under which the equilibrium allocation is efficient. I then analyze the design of surplus-maximizing segmentations, showing that the nature of search externalities determines when the constrained-efficient segmentation fully separates seller types or pools them into at most a binary partition.