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Participation of Artificial Intelligence in Economic Growth in Romania

Author

Listed:
  • Valeriu Ioan-Franc

    (Costin C. Kiritescu National Institute for Economic Research - Romanian Academy, Bucharest, Romania)

  • Ioan I. Gaf-Deac

    (Costin C. Kiritescu National Institute for Economic Research - Romanian Academy, Bucharest, Romania)

Abstract

The purpose of this article is to demonstrate that it is necessary to model the connections of the Romanian economy for growth with the help of Artificial Intelligence (AI). That is why it is useful to align with the trends in the EU economy and on a global level to use innovative technologies, with the domestic economy having the opportunity to become excellent. It is a moment of opportunity for commitment in this regard, considering that Romania already has the IT infrastructure and the human resources with a real predisposition to AI. The article reports on the research carried out, by way of example, on a number of AI companies, and from the answers received and processed, real values emerge that reflect the potential of contributing to economic growth through AI. Our article presents a first-of-its-kind view of how AI investment and participation relate to domestic economic outcomes. It is estimated that, mainly, in Romania in the coming years, the expected economic growth can be registered on account of the activities coming from small and medium enterprises dominated by AI. As such, it is considered that the new AI economy will be able to be built and engaged in Romania to the extent that small and medium enterprises will show constructive behaviour, with evolutions based on innovation with the help of AI .

Suggested Citation

  • Valeriu Ioan-Franc & Ioan I. Gaf-Deac, 2024. "Participation of Artificial Intelligence in Economic Growth in Romania," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(67), pages 944-944, August.
    • Handle: RePEc:aes:amfeco:v:26:y:2024:i:67:p:944
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    References listed on IDEAS

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    1. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2021. "The Productivity J-Curve: How Intangibles Complement General Purpose Technologies," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 333-372, January.
    2. Lorenzo Caliendo & Giordano Mion & Luca David Opromolla & Esteban Rossi-Hansberg, 2020. "Productivity and Organization in Portuguese Firms," Journal of Political Economy, University of Chicago Press, vol. 128(11), pages 4211-4257.
    3. Anastassia Fedyk & James Hodson, 2023. "Trading on Talent: Human Capital and Firm Performance," Review of Finance, European Finance Association, vol. 27(5), pages 1659-1698.
    4. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    5. Brad Hershbein & Lisa B. Kahn, 2018. "Do Recessions Accelerate Routine-Biased Technological Change? Evidence from Vacancy Postings," American Economic Review, American Economic Association, vol. 108(7), pages 1737-1772, July.
    6. Maryam Farboodi & Roxana Mihet & Thomas Philippon & Laura Veldkamp, 2019. "Big Data and Firm Dynamics," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 38-42, May.
    7. Ajay Agrawal & Joshua S. Gans & Avi Goldfarb, 2019. "Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 31-50, Spring.
    8. Serguey Braguinsky & Atsushi Ohyama & Tetsuji Okazaki & Chad Syverson, 2021. "Product Innovation, Product Diversification, and Firm Growth: Evidence from Japan's Early Industrialization," American Economic Review, American Economic Association, vol. 111(12), pages 3795-3826, December.
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    Cited by:

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    Keywords

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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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