Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity at Scale

by Edward L. Glaeser, Hyunjin Kim, and Michael Luca
 
 

Overview — Data from online platforms ranging from Yelp to Zillow offer the potential for improved measurement of the local economy. This paper finds that Yelp data can predict business growth, as measured by the Census Bureau, before official statistics are released. Predictive power increases with population density, income, and education level.

Author Abstract

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% 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.

Paper Information