Big Data in Economics

Authors

Matthew Harding, University of California, Irvine
Jonathan Hersh, Chapman UniversityFollow

Document Type

Article

Publication Date

9-2018

Abstract

Big Data refers to data sets of much larger size, higher frequency, and often more personalized information. Examples include data collected by smart sensors in homes or aggregation of tweets on Twitter. In small data sets, traditional econometric methods tend to outperform more complex techniques. In large data sets, however, machine learning methods shine. New analytic approaches are needed to make the most of Big Data in economics. Researchers and policymakers should thus pay close attention to recent developments in machine learning techniques if they want to fully take advantage of these new sources of Big Data.

Comments

This article was originally published in IZA World of Labor in 2018. DOI: 10.15185/izawol.451

Recommended Citation

Harding, M., Hersh, J. Big Data in economics. IZA World of Labor 2018: 451 doi: 10.15185/izawol.451

Peer Reviewed

1

Copyright

The authors