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Artificial intelligence and unemployment: New insights

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  • Mihai Mutascu

    (LEO - Laboratoire d'Économie d'Orleans - UO - Université d'Orléans - UT - Université de Tours)

Abstract
This paper investigates the impact of artificial intelligence on unemployment in the most high-tech and developed countries, using a theoretical model that is also supported empirically. The empirical methodology follows a nonlinear approach by using panel threshold and GMM-system estimations. The dataset covers the period 1998–2016, and includes 23 countries.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Mihai Mutascu, 2021. "Artificial intelligence and unemployment: New insights," Post-Print hal-03528263, HAL.
    • Handle: RePEc:hal:journl:hal-03528263
    DOI: 10.1016/j.eap.2021.01.012
    Note: View the original document on HAL open archive server: https://univ-orleans.hal.science/hal-03528263
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    Cited by:

    1. Kexu Wu & Zhiwei Tang & Longpeng Zhang, 2022. "Population Aging, Industrial Intelligence and Export Technology Complexity," Sustainability, MDPI, vol. 14(20), pages 1-24, October.
    2. Mihai Mutascu & Scott W. Hegerty, 2023. "Predicting the contribution of artificial intelligence to unemployment rates: an artificial neural network approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(2), pages 400-416, June.
    3. Xianpu Xu & Yuchen Song, 2023. "Is There a Conflict between Automation and Environment? Implications of Artificial Intelligence for Carbon Emissions in China," Sustainability, MDPI, vol. 15(16), pages 1-22, August.
    4. Nguyen, Quoc Phu & Vo, Duc Hong, 2022. "Artificial intelligence and unemployment:An international evidence," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 40-55.
    5. Zambrano-Monserrate, Manuel A., 2024. "Labor dynamics and unions: An empirical analysis through Okun's Law," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 613-628.
    6. Madanaguli, Arun & Sjödin, David & Parida, Vinit & Mikalef, Patrick, 2024. "Artificial intelligence capabilities for circular business models: Research synthesis and future agenda," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    7. Louise Manning, 2024. "Innovating in an Uncertain World: Understanding the Social, Technical and Systemic Barriers to Farmers Adopting New Technologies," Challenges, MDPI, vol. 15(2), pages 1-20, June.
    8. Jingyi TIAN & Jun NAGAYASU, 2024. "AI and Financial Systemic Risk in the Global Market," TUPD Discussion Papers 55, Graduate School of Economics and Management, Tohoku University.
    9. Filippi, Emilia & Bannò, Mariasole & Trento, Sandro, 2023. "Automation technologies and their impact on employment: A review, synthesis and future research agenda," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    10. Jean-Philippe Deranty & Thomas Corbin, 2022. "Artificial Intelligence and work: a critical review of recent research from the social sciences," Papers 2204.00419, arXiv.org.

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    JEL classification:

    • F22 - International Economics - - International Factor Movements and International Business - - - International Migration
    • O17 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Formal and Informal Sectors; Shadow Economy; Institutional Arrangements
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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