Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change

Edward Glaeser, Hyunjin Kim and Michael Luca

No 24952, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: D22 O18 O30 R11 (search for similar items in EconPapers)
Date: 2018-08
New Economics Papers: this item is included in nep-pay and nep-ure
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