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Artificial intelligence and productivity: global evidence from AI patent and bibliometric data

Aleksandra Parteka and Aleksandra Kordalska

No 67, GUT FME Working Paper Series A from Faculty of Management and Economics, Gdansk University of Technology

Abstract: In this paper we analyse the relationship between technological innovation in the artificial intelligence (AI) domain and productivity. We embed recently released data on patents and publications related to AI in an augmented model of productivity growth, which we estimate for the OECD countries and compare to an extended sample including non-OECD countries. Our instrumental variable estimates, which account for AI endogeneity, provide evidence in favour of the modern productivity paradox. We show that the development of AI technologies remains a niche innovation phenomenon with a negligible role in the officially recorded productivity growth process. This general result, i.e. a lack of a strong relationship between AI and macroeconomic productivity growth, is robust to changes in the country sample, in the way we quantify labour productivity and technology (including AI stock), in the specification of the empirical model (control variables) and in estimation methods.

Keywords: technological innovation; productivity paradox; productivity growth; artificial intelligence; patents (search for similar items in EconPapers)
JEL-codes: O33 O47 (search for similar items in EconPapers)
Date: 2022-01, Revised 2022-09
New Economics Papers: this item is included in nep-big, nep-cse, nep-eff, nep-gro, nep-ict, nep-ino, nep-ipr, nep-sbm and nep-tid
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https://cdn.files.pg.edu.pl/zie/Strona%20polska/Na ... arteka_Kordalska.pdf Revised version, 2022 (application/pdf)

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Journal Article: Artificial intelligence and productivity: global evidence from AI patent and bibliometric data (2023) Downloads
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