Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change

13 Pages Posted: 19 Feb 2018  

Edward L. Glaeser

Harvard University - Department of Economics; Brookings Institution; National Bureau of Economic Research (NBER)

Hyunjin Kim

Harvard Business School

Michael Luca

Harvard Business School

Date Written: February 19, 2018

Abstract

Data from digital platforms have the potential to improve our understanding of gentrification and enable new measures of how neighborhoods change in close to real time. Combining data on businesses from Yelp with data on gentrification from the Census, Federal Housing Finance Agency, and Streetscore (an algorithm using Google Streetview), we find that gentrifying neighborhoods tend to have growing numbers of local groceries, cafes, restaurants, and bars, with little evidence of crowd-out of other types of businesses. For example, the entry of a new coffee shop into a zip code in a given year is associated with a 0.5 percent increase in housing prices. Moreover, Yelp measures of local business activity provide leading indicators for housing price changes and help to forecast which neighborhoods are gentrifying.

Suggested Citation

Glaeser, Edward L. and Kim, Hyunjin and Luca, Michael, Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change (February 19, 2018). Harvard Business School NOM Unit Working Paper No. 18-077. Available at SSRN: https://ssrn.com/abstract=3123733 or http://dx.doi.org/10.2139/ssrn.3123733

Edward L. Glaeser

Harvard University - Department of Economics ( email )

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Brookings Institution

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National Bureau of Economic Research (NBER)

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Hyunjin Kim

Harvard Business School ( email )

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Michael Luca (Contact Author)

Harvard Business School ( email )

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Boston, MA 02163
United States

HOME PAGE: http://drfd.hbs.edu/fit/public/facultyInfo.do?facInfo=ovr&facId=602417

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