iBuyer vs Agent: Transaction Mechanism for Housing Market

Chenhao Zhang, Yixin Lu and Luyi Gui

Abstract

The advent of instant buyers (iBuyers)---online platforms that leverage technology to make instant cash offers to homeowners---has revolutionized the way homes are sold, which traditionally involves lengthy agent-mediated sales processes. However, evidence from practice suggests that while iBuyers' speedy transaction attracts home sellers, it does not allow for thorough inspection, which causes iBuyers to rely on seller-reported property information when generating cash offers. Such information asymmetry exposes iBuyers to adverse selection. In this paper, we adopt a signaling game framework to examine the profit implications of this tradeoff and how it may be mitigated. Equilibrium analysis indicates that an iBuyer can be more profitable than if the platform adopts traditional agent-mediated home sales instead. This happens when the iBuyer possesses sufficient market power to resell the acquired homes at competitive prices. Otherwise, the iBuyer may not be able to break even due to adverse selection. We show that this issue can be effectively addressed if the iBuyer introduces ex-post payments to sellers contingent on the resale price---akin to the commission-based payment under the traditional agent-mediated sales---and adjusts the instant cash offer accordingly. Contextualizing our findings based on a case study of major housing markets in the U.S. with active iBuyer presence illustrates substantial potential of this hybrid approach in improving iBuyers' profits. By contrast, we find that contract menu design---a common approach to address information asymmetry---can be expensive to implement due to adverse selection and may erode profits for iBuyers with limited market power.

Major revision at Management Science, draft available upon request