Working Paper: NBER ID: w24952
Authors: Edward L. Glaeser; Hyunjin Kim; Michael Luca
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.
Keywords: Gentrification; Yelp Data; Neighborhood Change; Housing Prices; Urban Economics
JEL Codes: D22; O18; O30; R11
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Starbucks openings (M13) | housing price growth (R31) |
| growth in number of cafes (O49) | housing price growth (R31) |
| growth of grocery stores, restaurants, and bars (L81) | housing price growth (R31) |
| exogenous neighborhood changes (R23) | store openings (L81) |
| store openings (L81) | housing price growth (R31) |