Publications
Publications
- 2017
- HBS Working Paper Series
Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity
By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
Abstract
Can new data sources from online platforms help to measure local economic activity? Government datasets from agencies such as the U.S. Census Bureau provide the standard measures of economic activity at the local level. However, these statistics typically appear only after multiyear lags, and the public-facing versions are aggregated to the county or ZIP code level. In contrast, crowdsourced data from online platforms such as Yelp are often contemporaneous and geographically finer than official government statistics. In this paper, we present evidence that Yelp data can complement government surveys by measuring economic activity in close to real time, at a granular level, and at almost any geographic scale. Changes in the number of businesses and restaurants reviewed on Yelp can predict changes in the number of overall establishments and restaurants in County Business Patterns (CBP). An algorithm using contemporaneous and lagged Yelp data can explain 29.2% of the residual variance after accounting for lagged CBP data, in a testing sample not used to generate the algorithm. The algorithm is more accurate for denser, wealthier, and more educated ZIP codes.
Keywords
Citation
Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity." Harvard Business School Working Paper, No. 18-022, September 2017. (Revised October 2017.)