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来源类型Working Paper
规范类型报告
DOI10.3386/w24010
来源IDWorking Paper 24010
Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity
Edward L. Glaeser; Hyunjin Kim; Michael Luca
发表日期2017-11-13
出版年2017
语种英语
摘要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 local 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, 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. An algorithm using contemporaneous and lagged Yelp data can 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 algorithm is more accurate for denser, wealthier, and more educated ZIP codes.
主题Macroeconomics ; Macroeconomic Models ; Development and Growth ; Innovation and R& ; D ; Regional and Urban Economics ; Regional Economics
URLhttps://www.nber.org/papers/w24010
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/581684
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Edward L. Glaeser,Hyunjin Kim,Michael Luca. Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity. 2017.
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