What Online Searches Reveal About Home Prices
Cities where people search unusually hard for real estate go on to see unusually strong home price growth.
Before anyone buys a house, they search for one, and increasingly that search starts online. Each query leaves a trace, and in aggregate those traces amount to a record of intentions. This research asks whether that record can forecast housing markets.
Using online search data on real estate queries across U.S. cities, the study examines whether abnormal search intensity in one period predicts cross-sectional differences in home price changes across cities in later periods.
It does, and the magnitudes are economically meaningful. Cities with abnormally high real estate search intensity go on to outperform cities with abnormally low search volume by as much as 8.5 percent over a two-year horizon.
The paper, which received the American Real Estate Society's best paper award in the housing category, sits in an early wave of research showing that collective online behavior can anticipate market outcomes, from stock trading volume to, here, the value of the roof over your head.
The Takeaway
Aggregated online search is a database of intentions. Cities where real estate searches spike see stronger subsequent home price appreciation, by as much as 8.5 percent over two years.