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Big Data in economics

Jonathan Hersh and Matthew Harding ()

IZA World of Labor, 2018, No 451, 451

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.

Keywords: Big Data; machine learning; prediction; causal inference (search for similar items in EconPapers)
JEL-codes: C55 C8 (search for similar items in EconPapers)
Date: 2018
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