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Big Data in economics

Author

Listed:
  • Jonathan Hersh

    (Chapman University, USA)

  • Matthew Harding

    (University of California, Irving, USA)

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.

Suggested Citation

  • Jonathan Hersh & Matthew Harding, 2018. "Big Data in economics," IZA World of Labor, Institute of Labor Economics (IZA), pages 451-451, September.
    • Handle: RePEc:iza:izawol:journl:2018:n:451
    as

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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Ana Cecilia Quiroga Gutierrez & Daniel J. Lindegger & Ala Taji Heravi & Thomas Stojanov & Martin Sykora & Suzanne Elayan & Stephen J. Mooney & John A. Naslund & Marta Fadda & Oliver Gruebner, 2023. "Reproducibility and Scientific Integrity of Big Data Research in Urban Public Health and Digital Epidemiology: A Call to Action," IJERPH, MDPI, vol. 20(2), pages 1-15, January.
    2. Qin, Fei & Wu, Steven Y., 2022. "Estimating Consumer Segments and Choices from Limited Information: The Application of Machine Learning Methods," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322473, Agricultural and Applied Economics Association.
    3. Mehmet Güney Celbiş, 2021. "A machine learning approach to rural entrepreneurship," Papers in Regional Science, Wiley Blackwell, vol. 100(4), pages 1079-1104, August.
    4. Ajit Desai, 2023. "Machine Learning for Economics Research: When What and How?," Papers 2304.00086, arXiv.org, revised Apr 2023.

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    More about this item

    Keywords

    Big Data; machine learning; prediction; causal inference;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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