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Sources and Types of Big Data for Macroeconomic Forecasting

Philip Garboden ()
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Philip Garboden: Department of Urban and Regional Planning, University of Hawai‘i at Manoa

No 2019-3, Working Papers from University of Hawaii Economic Research Organization, University of Hawaii at Manoa

Abstract: This chapter considers the types of Big Data that have proven useful for macroeconomic forecasting. It first presents the various definitions of Big Data, proposing one we believe is most useful for forecasting. The literature on both the opportunities and challenges of Big Data are presented. It then proposes a taxonomy of the types of Big Data: 1) Financial Market Data; 2) E-Commerce and Credit Cards; 3) Mobile Phones; 4) Search; 5) Social Media Data; 6) Textual Data; 7) Sensors, and The Internet of Things; 8) Transportation Data; 9) Other Administrative Data. Noteworthy studies are described throughout.

Keywords: big data; data sources (search for similar items in EconPapers)
JEL-codes: C80 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-big, nep-mac and nep-pay
Date: 2019-07
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http://www.uhero.hawaii.edu/assets/UHEROwp1903.pdf First version, 2019 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:hae:wpaper:2019-3

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