Online Property Valuation, Price Discovery, and Market Efficiency in the Housing Market

Jeonghyun Chung, Georgia State University


This paper studies the impact of publicly available property valuation on price discovery and sales outcomes in the housing markets using Zestimate, a popular property value estimate provided by the largest PropTech firm in the U.S. I find that sellers list their houses at inflated prices over the predicted values when their Zestimates are biased upwards. This initial overpricing leads to a subsequent 2 percent reduction in listing prices and delays sale by 3 days on average. However, such properties are eventually sold at a higher price than similar houses with undervalued Zestimates. On the other hand, sellers of properties with overvalued Zestimates are more likely to withdraw their homes from the market due to overpricing. My findings suggest that while easy public access to property value estimates should in theory improve market efficiency, inaccurate valuation can in fact have the opposite effect as market participants rely heavily on online property values in their decision-making.