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Why Is Intermediating Houses So Difficult? Evidence from iBuyers

Greg Buchak^1,2,3,4,5; Gregor Matvos^1,2,3,4,5; Tomasz Piskorski^1,2,3,4,5; Amit Seru^1,2,3,4,5

¹ Northwestern University · ² National Bureau of Economic Research · ³ National University of Singapore · ⁴ Palo Alto University · ⁵ Stanford University

We study the frictions in dealer-intermediation in residential real estate through the lens of "iBuyers," technology entrants, who purchase and sell residential real estate through online platforms. iBuyers supply liquidity to households by allowing them to avoid a lengthy sale process. They sell houses quickly and earn a 5% spread. Their prices are well explained by a simple hedonic model, consistent with their use of algorithmic pricing. iBuyers choose to intermediate in markets that are liquid, and in which automated valuation models have low pricing error. These facts suggest that iBuyers' speedy offers may come at the cost of information loss concerning house attributes that are difficult to capture in an algorithm, resulting in adverse selection. We calibrate a dynamic structural search model with adverse selection to understand and quantify the economic forces underlying the tradeoffs of dealer intermediation in this market.

DOI

10.1086/742710

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en

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