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How natural field experiments have enhanced our understanding of unemployment

Author

Listed:
  • Omar Al-Ubaydli

    (Bahrain Center for Strategic, International and Energy Studies
    George Mason University
    King Fahad University of Petroleum and Minerals)

  • John A. List

    (University of Chicago
    NBER)

Abstract

Natural field experiments investigating key labour market phenomena such as unemployment have only been used since the early 2000s. This paper reviews the literature and draws three primary conclusions that deepen our understanding of unemployment. First, the inability to monitor workers perfectly in many occupations complicates the hiring decision in a way that contributes to unemployment. Second, the inability to determine a worker’s attributes precisely at the time of hiring leads to discrimination on the basis of factors such as race, gender, age and ethnicity. This can lead to systematically high and persistent levels of unemployment for groups that face discrimination. Third, the importance of social and personal dynamics in the workplace can lead to short-term unemployment. Much of the knowledge necessary for these conclusions could only be obtained using natural field experiments due to their ability to combine randomized control with an absence of experimenter demand effects.

Suggested Citation

  • Omar Al-Ubaydli & John A. List, 2019. "How natural field experiments have enhanced our understanding of unemployment," Nature Human Behaviour, Nature, vol. 3(1), pages 33-39, January.
    • Handle: RePEc:nat:nathum:v:3:y:2019:i:1:d:10.1038_s41562-018-0496-z
    DOI: 10.1038/s41562-018-0496-z
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    Cited by:

    1. John A. List, 2024. "Optimally generate policy-based evidence before scaling," Nature, Nature, vol. 626(7999), pages 491-499, February.
    2. John List, 2022. "2021 Summary Data of Natural Field Experiments Published on Fieldexperiments.com," Natural Field Experiments 00747, The Field Experiments Website.
    3. Omar Al-Ubaydli & Faith Fatchen & John List, 2025. "Using Field Experiments to Understand the Impact of Institutions on Economic Growth," Springer Books, in: Claude Ménard & Mary M. Shirley (ed.), Handbook of New Institutional Economics, edition 0, chapter 42, pages 1117-1143, Springer.
    4. Buchanan, Joy & Houser, Daniel, 2022. "If wages fell during a recession," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 1141-1159.
    5. Rongwang Guo & Jianxiu Wang & Yuntian You, 2024. "The impact of multiple discrimination on labor misallocation of China: Based on fsQCA method," PLOS ONE, Public Library of Science, vol. 19(8), pages 1-13, August.
    6. John List, 2021. "2021 Summary Data of Artefactual Field Experiments Published on Fieldexperiments.com," Artefactual Field Experiments 00749, The Field Experiments Website.
    7. Brit Grosskopf & Graeme Pearce, 2020. "Do You Mind Me Paying Less? Measuring Other-Regarding Preferences in the Market for Taxis," Management Science, INFORMS, vol. 66(11), pages 5059-5074, November.
    8. John List, 2022. "Framed Field Experiments: 2021 Summary on Fieldexperiments.com," Framed Field Experiments 00752, The Field Experiments Website.

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