Jonathan Hersh, PhD

IZA World of Labor

Big Data in Economics

Matthew Harding · Jonathan Hersh ·

Explains how high-frequency, high-volume data and machine learning methods are transforming empirical economics and policy design.

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.

How to cite this paper

APA

Harding, M., & Hersh, J. (2018). Big Data in Economics. IZA World of Labor. https://www.econstor.eu/handle/10419/193433

BibTeX

@article{harding2018data,
  title   = {Big Data in Economics},
  author  = {Harding, Matthew and Hersh, Jonathan},
  journal = {IZA World of Labor},
  year    = {2018},
  url     = {https://www.econstor.eu/handle/10419/193433}
}

Publication details

VenueIZA World of Labor
Year2018
AuthorsMatthew Harding, Jonathan Hersh
Published versionhttps://www.econstor.eu/handle/10419/193433

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