Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change
We demonstrate that data from digital platforms such as Yelp have the potential to improve our understanding of gentrification, both by providing data in close to real time (i.e. nowcasting and forecasting) and by providing additional context about how the local economy is changing. Combining Yelp and Census data, we find that gentrification, as measured by changes in the educational, age, and racial composition within a ZIP code, is strongly associated with increases in the numbers of grocery stores, cafes, restaurants, and bars, with little evidence of crowd-out of other categories of businesses. We also find that changes in the local business landscape is a leading indicator of housing price changes, and that the entry of Starbucks (and coffee shops more generally) into a neighborhood predicts gentrification. Each additional Starbucks that enters a zip code is associated with a 0.5% increase in housing prices.
We thank Byron Perpetua for excellent research assistance. We thank Susan Athey, Shane Greenstein, and Luther Lowe for valuable feedback, and Yelp for providing data for this analysis. Kim and Luca have done consulting for tech companies including Yelp, but their compensation and ability to publish are not tied to the results of this paper. All remaining errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Edward L. Glaeser
I have received speaking fees from organizations that organize members that invest in real estate markets, including the National Association of Real Estate Investment Managers and the Pension Real Estate Association.