56 Pages Posted: 18 Sep 2017
Date Written: September 15, 2017
Can new data sources from online platforms help to measure local economic activity at scale? Government datasets from agencies such as the U.S. Census Bureau have long been the gold standard for measuring economic activity at the local level. However, these statistics typically appear only after multi-year 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. We find that changes in the number of businesses and restaurants reviewed on Yelp can help to predict changes in the number of overall establishments and restaurants in County Business Patterns. Contemporaneous and lagged Yelp data can generate an algorithm that is able to explain 29.2 percent of the residual variance after accounting for lagged CBP data, in a testing sample not used to generate the algorithm. The nowcasting results are more accurate for denser, wealthier, and more educated ZIP codes.
Suggested Citation: Suggested Citation
Glaeser, Edward L. and Kim, Hyunjin and Luca, Michael, Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity at Scale (September 15, 2017). Harvard Business School NOM Unit Working Paper No. 18-022. Available at SSRN: https://ssrn.com/abstract=3037603