Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/244249 
Year of Publication: 
2020
Series/Report no.: 
Working Paper No. 2020-35
Publisher: 
Federal Reserve Bank of Chicago, Chicago, IL
Abstract: 
The use of "Big Data" to explain fluctuations in the broader economy or guide the business decisions of a firm is now so commonplace that in some instances it has even begun to rival more traditional government statistics and business analytics. Big data sources can very often provide advantages when compared to these more traditional data sources, but with these advantages also comes the potential for pitfalls. We lay out a framework called SMALL that we have developed in order to help interested parties as they navigate the big data minefield. Based on a set of five questions, the SMALL framework should help users of big data spot concerns in their own work and that of others who rely on such data to draw conclusions with actionable public policy or business implications. To demonstrate, we provide several case studies that show a healthy dose of skepticism can be warranted when working with and interpreting these new big data sources.
Subjects: 
big data
economic statistics
business analytics
forecasting
JEL: 
C53
C55
C80
C81
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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