Founded in 1920, the NBER is a private, non-profit, non-partisan organization dedicated to conducting economic research and to disseminating research findings among academics, public policy makers, and business professionals.

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.

Open banking (OB) empowers bank customers to share their financial transaction data with fintechs and other banks. New cross-country data shows 49 countries adopted OB policies, privacy preferences predict policy adoption, and adoption spurs fintech entry. UK microdata shows that OB enables: (i) consumers to access both financial advice and credit; (ii) SMEs to establish new lending relationships. In a calibrated model, OB universally improves welfare through entry and product improvements when used for advice. When used for credit, OB promotes entry and competition by reducing adverse selection, but higher prices for costlier or privacy-conscious consumers partially offset these benefits.