Why is Intermediating Houses so Difficult? Evidence from iBuyers

Greg Buchak, Gregor Matvos, T. Piskorski, Amit Seru
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引用次数: 14

Abstract

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 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 the economic forces underlying the tradeoffs of dealer intermediation in this market. The model reveals the central tradeoff to intermediating in residential real estate. To provide valuable liquidity service, transactions must be closed quickly. Yet, the intermediary must also be able to price houses precisely to avoid adverse selection, which is difficult to accomplish quickly. Low underlying liquidity exacerbates adverse selection. Our analysis suggests that iBuyers’ technology provides a middle ground: they can transact quickly limiting information loss. Even with this technology, intermediation is only profitable in the most liquid and easy to value houses. Therefore, iBuyers’ technology allows them to supply liquidity, but only in pockets where it is least valuable. We also find limited scope for dealer intermediation even with improved pricing technology, suggesting that underlying liquidity will be an impediment for intermediation in the future.
居间中介为何如此困难?来自iBuyers的证据
我们通过“iBuyers”(通过在线平台购买和销售住宅房地产的技术进入者)的视角,研究了住宅房地产交易中介中的摩擦。买家通过让家庭避免漫长的销售过程,为家庭提供流动性。他们卖房很快,赚取5%的差价。它们的价格可以用一个简单的享乐模型很好地解释,与它们使用的算法定价一致。买家选择在流动性强、自动估值模型定价误差小的市场中进行中间交易。这些事实表明,买家快速出价的代价是有关房屋属性的信息丢失,而这些信息难以用算法捕获,从而导致逆向选择。我们校准了一个具有逆向选择的动态结构搜索模型,以了解该市场中经销商中介权衡背后的经济力量。该模型揭示了住宅房地产中介的核心权衡。为了提供有价值的流动性服务,交易必须迅速结束。然而,中介还必须能够准确地为房屋定价,以避免逆向选择,这很难迅速完成。潜在流动性低加剧了逆向选择。我们的分析表明,iBuyers的技术提供了一个中间地带:他们可以快速交易,限制信息丢失。即使有了这种技术,中介也只能在流动性最强、最容易估值的房屋中获利。因此,iBuyers的技术允许他们提供流动性,但只在最不值钱的地方。我们还发现,即使定价技术得到改进,交易商中介的范围也有限,这表明潜在的流动性将成为未来中介的障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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