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Artificial intelligence and unemployment: New insights

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  • Mutascu, Mihai

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.

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  • Mutascu, Mihai, 2021. "Artificial intelligence and unemployment: New insights," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 653-667.
    • Handle: RePEc:eee:ecanpo:v:69:y:2021:i:c:p:653-667
    DOI: 10.1016/j.eap.2021.01.012
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    1. Daron Acemoglu & Pascual Restrepo, 2020. "The wrong kind of AI? Artificial intelligence and the future of labour demand," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 25-35.
    2. Joseph Zeira, 1998. "Workers, Machines, and Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1091-1117.
    3. Miles S. Kimball & John G. Fernald & Susanto Basu, 2006. "Are Technology Improvements Contractionary?," American Economic Review, American Economic Association, vol. 96(5), pages 1418-1448, December.
    4. Francesco Chiacchio & Georgios Petropoulos & David Pichler, 2018. "The impact of industrial robots on EU employment and wages- A local labour market approach," Working Papers 25186, Bruegel.
    5. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    6. Marco Gallegati & Mauro Gallegati & James B. Ramsey & Willi Semmler, 2014. "Does Productivity Affect Unemployment? A Time-Frequency Analysis for the US," Dynamic Modeling and Econometrics in Economics and Finance, in: Marco Gallegati & Willi Semmler (ed.), Wavelet Applications in Economics and Finance, edition 127, pages 23-46, Springer.
    7. Südekum, Jens & Dauth, Wolfgang & Findeisen, Sebastian & Woessner, Nicole, 2017. "German Robots – The Impact of Industrial Robots on Workers," CEPR Discussion Papers 12306, C.E.P.R. Discussion Papers.
    8. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," Boston University - Department of Economics - Working Papers Series dp-297, Boston University - Department of Economics.
    9. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    10. Gries, Thomas & Naude, Wim, 2018. "Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter?," MERIT Working Papers 2018-047, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    11. Qunyong Wang, 2015. "Fixed-effect panel threshold model using Stata," Stata Journal, StataCorp LP, vol. 15(1), pages 121-134, March.
    12. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    13. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    14. M. Hashem Pesaran & Aman Ullah & Takashi Yamagata, 2008. "A bias-adjusted LM test of error cross-section independence," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 105-127, March.
    15. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    16. James Bessen, 2018. "AI and Jobs: the role of demand," NBER Working Papers 24235, National Bureau of Economic Research, Inc.
    17. Carbonero, Francesco. & Ernst, Ekkehard & Weber, Enzo., 2018. "Robots worldwide the impact of automation on employment and trade," ILO Working Papers 995008793402676, International Labour Organization.
    18. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    19. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    20. Bai, Jushan, 1997. "Estimating Multiple Breaks One at a Time," Econometric Theory, Cambridge University Press, vol. 13(3), pages 315-352, June.
    21. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    22. Sune Karlsson & Nannan Lundin & Fredrik Sjöholm & Ping He, 2009. "Foreign Firms and Chinese Employment," The World Economy, Wiley Blackwell, vol. 32(1), pages 178-201, January.
    23. Bharat Trehan, 2003. "Productivity shocks and the unemployment rate," Economic Review, Federal Reserve Bank of San Francisco, pages 13-27.
    24. Morgan R. Frank & David Autor & James E. Bessen & Erik Brynjolfsson & Manuel Cebrian & David J. Deming & Maryann Feldman & Matthew Groh & José Lobo & Esteban Moro & Dashun Wang & Hyejin Youn & Iyad Ra, 2019. "Toward understanding the impact of artificial intelligence on labor," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(14), pages 6531-6539, April.
    25. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    26. Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2017. "Revisiting the risk of automation," Economics Letters, Elsevier, vol. 159(C), pages 157-160.
    27. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    28. Marco Gallegati & Willi Semmler (ed.), 2014. "Wavelet Applications in Economics and Finance," Dynamic Modeling and Econometrics in Economics and Finance, Springer, edition 127, number 978-3-319-07061-2, May.
    29. Fujii, Hidemichi & Managi, Shunsuke, 2018. "Trends and priority shifts in artificial intelligence technology invention: A global patent analysis," Economic Analysis and Policy, Elsevier, vol. 58(C), pages 60-69.
    30. Ernst Ekkehardt & Merola Rossana & Samaan Daniel, 2019. "Economics of Artificial Intelligence: Implications for the Future of Work," IZA Journal of Labor Policy, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 9(1), pages 1-35, June.
    31. Robert J. Gordon, 2018. "Why Has Economic Growth Slowed When Innovation Appears to be Accelerating?," NBER Working Papers 24554, National Bureau of Economic Research, Inc.
    32. Abiodun O. Folawewo & Oluwafemi M. Adeboje, 2017. "Macroeconomic Determinants of Unemployment: Empirical Evidence from Economic Community of West African States," African Development Review, African Development Bank, vol. 29(2), pages 197-210, June.
    33. A. W. Phillips, 1958. "The Relation Between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861–1957," Economica, London School of Economics and Political Science, vol. 25(100), pages 283-299, November.
    34. Bertin Martens & Songül Tolan, 2018. "Will this time be different? A review of the literature on the Impact of Artificial Intelligence on Employment, Incomes and Growth," JRC Working Papers on Digital Economy 2019-04, Joint Research Centre (Seville site).
    35. Bertin Martens & Songul Tolan, 2018. "Will this time be different? A review of the literature on the Impact of Artificial Intelligence on Employment, Incomes and Growth," JRC Working Papers on Digital Economy 2018-08, Joint Research Centre.
    36. Joseph E. Stiglitz, 2014. "Unemployment and Innovation," NBER Working Papers 20670, National Bureau of Economic Research, Inc.
    37. Gordon, Robert J., 2018. "Why Has Economic Growth Slowed When Innovation Appears To Be Accelerating?," CEPR Discussion Papers 13039, C.E.P.R. Discussion Papers.
    38. Trevor Breusch, 2005. "Estimating the Underground Economy using MIMIC Models," Econometrics 0507003, University Library of Munich, Germany, revised 15 Dec 2005.
    39. Fatima, Samar & Desouza, Kevin C. & Dawson, Gregory S., 2020. "National strategic artificial intelligence plans: A multi-dimensional analysis," Economic Analysis and Policy, Elsevier, vol. 67(C), pages 178-194.
    40. Dauth, Wolfgang & Findeisen, Sebastian & Südekum, Jens & Wößner, Nicole, 2017. "German robots - the impact of industrial robots on workers," IAB-Discussion Paper 201730, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    41. Horst Feldmann, 2006. "Government Size and Unemployment: Evidence from Industrial Countries," Public Choice, Springer, vol. 127(3), pages 443-459, June.
    42. Cobus Vermeulen, 2015. "Inflation, growth and employment in South Africa: Trends and trade-offs," Working Papers 547, Economic Research Southern Africa.
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    2. 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.
    3. 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.
    4. Kexu Wu & Zhiwei Tang & Longpeng Zhang, 2022. "Population Aging, Industrial Intelligence and Export Technology Complexity," Sustainability, MDPI, vol. 14(20), pages 1-24, October.
    5. 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.
    6. 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.
    7. 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.
    8. 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).
    9. 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.
    10. 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.

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    More about this item

    Keywords

    Artificial intelligence; Unemployment; Implications; High-tech countries;
    All these keywords.

    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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