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Magazine publication

Type:

Magazine publication

Published in:

TECHNOVATION no. 125,
ISSN: 0166-4972

Publication year:

2023

Bibliographic description:

Parteka A, Kordalska A. (2023). Artificial intelligence and productivity: global evidence from AI patent and bibliometric data. Technovation. Elsevier. 125 (2023) 102764

DOI:

Digital Object Identifier (open in new tab) 10.1016/j.technovation.2023.102764

Bibliography: test

1. Acemoglu, D., Restrepo, P., 2018. The race between man and machine: implications of technology for growth, factor shares, and employment. Am. Econ. Rev. 108 (6), 1488-1542. open in new tab
2. Acemoglu, D., Dorn, D., Hanson, G.H., Price, B., 2014. Return of the Solow paradox? IT, productivity, and employment in US manufacturing. Am. Econ. Rev. 104 (5), 394-399. open in new tab
3. Acemoglu, D., Johnson, S., Robinson, J.A., 2005. Institutions as a fundamental cause of long-run growth. In: Aghion, P., Durlauf, S.N. (Eds.), Handbook of Economic Growth, ume 1A. North. open in new tab
4. Acemoglu, D., Lelarge, C., Restrepo, P., 2020. Competing with robots: firm-level evidence from France. AEA Papers and Proceedings 110, 383-388. open in new tab
5. Aghion, P., Jones, B.F., Jones, C.I., 2019. In: Agrawal, Gans, Goldfarb] (Eds.), Artificial Intelligence and Economic Growth. inThe Economics of Artificial Intelligence: an Agenda, pp. 237-290 (Chapter 9). open in new tab
6. Aghion, P., Howitt, P., 1992. A model of growth through creative destruction. Econometrica 60 (2), 323-351. open in new tab
7. Agrawal, A., McHale, J., Oettl, A., 2019. Finding needles in haystacks: artificial intelligence and recombinant growth. In: Agrawal, A., Gans, J., Goldfarb, A. (Eds.), The Economics of Artificial Intelligence: an Agenda. University of Chicago Press, Chicago. open in new tab
8. Archibugi, D., Pianta, M., 1992. The Technological Specialization of Advanced Countries: A Report to the EEC on International Science and Technology Activities, 13188. Springer Science & Business Media. open in new tab
9. Ballestar, M.T., Díaz-Chao, Á ., Sainz, J., Torrent-Sellens, J., 2020. Knowledge, robots and productivity in SMEs: explaining the second digital wave. J. Bus. Res. 108, 119-131. open in new tab
10. Barro, R.J., Lee, J.W., 2013. A new data set of educational attainment in the world, 1950-2010. J. Dev. Econ. 104, 184-198. open in new tab
11. Baruffaldi, S., van Beuzekom, B., Dernis, H., Harhoff, D., Rao, N., Rosenfeld, D., Squicciarini, M., 2020. Identifying and measuring developments in artificial intelligence: making the impossible possible. In: OECD Science, Technology and Industry Working Papers, No. 2020/05. OECD Publishing, Paris. https://doi.org/ 10.1787/5f65ff7e-en. open in new tab
12. Bassetti, T., Borbon Galvez, Y., Del Sorbo, M., Pavesi, F., 2020. Artificial Intelligence - Impact on Total Factor Productivity, E-Commerce & Fintech. EUR 30428 EN, Publications Office of the European Union, Luxembourg. https://doi.org/10.2760/ 333292,JRC122268, 978-92-76-24693-0. open in new tab
13. Belderbos, R.A., Kazimierczak, M., Goedhuys, M., 2022. Trademarks, patents and the appropriation strategies of incumbents: the scope of new firm formation in European regions. Reg. Stud. 56 (2), 210-226. https://doi.org/10.1080/ 00343404.2021.1947486. open in new tab
14. Benassi, M., Grinza, E., Rentocchini, F., Rondi, L., 2022. Patenting in 4IR technologies and firm performance. Ind. Corp. Change 31 (1), 112-136. open in new tab
15. Bloom, N., Jones, C.I., Van Reenen, J., Webb, M., 2020. Are ideas getting harder to find? Am. Econ. Rev. 110 (4), 1104-1144. open in new tab
16. Botev, J., et al., 2019. A new macroeconomic measure of human capital with strong empirical links to productivity. In: OECD Economics Department Working Papers, No. 1575. OECD Publishing, Paris. https://doi.org/10.1787/d12d7305-en. open in new tab
17. Bresnahan, T.F., Trajtenberg, M., 1995. General purpose technologies 'Engines of growth. J. Econom. 65 (1), 83-108. open in new tab
18. Brynjolfsson, E., Rock, D., Syverson, C., 2019. artificial intelligence and the modern productivity paradox: a clash of expectations and statistics. In: Agrawal, Gans, Goldfarb (Eds.), The Economics of Artificial Intelligence: an Agenda, pp. 23-60 (Chapter 1). open in new tab
19. Brynjolfsson, E., 1993. The productivity paradox of information technology. Commun. ACM 36 (12), 66-77. open in new tab
20. Brynjolfsson, E., McAfee, A., 2014. The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W.W. Norton & Co, New York.
21. Brynjolfsson, E., Rock, D., Syverson, C., 2021. The productivity J-curve: how intangibles complement general purpose technologies. Am. Econ. J. Macroecon. 13 (1), 333-372. open in new tab
22. Buccirossi, P., Ciari, L., Duso, T., Spagnolo, G., Vitale, C., 2013. Competition policy and productivity growth: an empirical assessment. Rev. Econ. Stat. 95 (4), 1324-1336. open in new tab
23. Bughin, J., Seong, J., Manyika, J., Chui, M., Joshi, R., 2018. Notes from the AI Frontier: Modeling the Impact of AI on the World Economy. McKinsey Global Institute.
24. Byrne, D.M., Fernald, J.G., Reinsdorf, M.B., 2016. Does the United States have a productivity slowdown or a measurement problem? Brookings Pap. Econ. Activ. 2016 (1), 109-182. open in new tab
25. Castellani, D., Lamperti, F., Lavoratori, K., 2022. Measuring adoption of industry 4.0 technologies via international trade data: insights from European countries. Journal of Industrial and Business Economics 49 (1), 51-93. open in new tab
26. Ceccobelli, M., Gitto, S., Mancuso, P., 2012. ICT capital and labour productivity growth: a non-parametric analysis of 14 OECD countries. Telecommun. Pol. 36 (4), 282-292. open in new tab
27. Corrado, C., Haskel, J., Jona-Lasinio, C., 2021. Artificial intelligence and productivity: an intangible assets approach. Oxf. Rev. Econ. Pol. 37 (3), 435-458. open in new tab
28. Corrado, C., Hulten, C., Sichel, D., 2009. Intangible capital and US economic growth. Rev. Income Wealth 55 (3), 661-685. open in new tab
29. Crafts, N., 2004. Productivity growth in the industrial revolution: a new growth accounting perspective. J. Econ. Hist. 64 (2), 521-535. open in new tab
30. Crafts, N., 2018. The productivity slowdown: is it the 'new normal. Oxf. Rev. Econ. Pol. 34 (3), 443-460. open in new tab
31. Crafts, N., Mills, T.C., 2020. Is the UK productivity slowdown unprecedented? Natl. Inst. Econ. Rev. 251, R47-R53. open in new tab
32. Cugno, M., Castagnoli, R., Büchi, G., Pini, M., 2022. Industry 4.0 and production recovery in the covid era. Technovation 114, 102443. open in new tab
33. Dalla Benetta, A., Sobolewski, M., Nepelski, D., 2021. AI Watch: 2020 EU AI Investments. EUR 30826 EN, Publications Office of the European Union, Luxembourg, p. JRC126477. https://doi.org/10.2760/017514, 2021, ISBN 978-92-76-41492-6. open in new tab
34. Damioli, G., Van Roy, V., Vertesy, D., 2021. The impact of artificial intelligence on labor productivity. Eurasian Business Review 11 (1), 1-25. open in new tab
35. Dernis, H., Gkotsis, P., Grassano, N., Nakazato, S., Squicciarini, M., van Beuzekom, B., Vezzani, A., 2019. World Corporate Top R&D Investors: Shaping The Future of Technologies and of AI(No. JRC117068). Joint Research Centre (Seville site).
36. Elstner, S., Feld, L.P., Schmidt, C.M., 2018. The German Productivity Paradox-Facts and Explanations. CESifo Working Paper No. 7231, Available at: SSRN: https://ssrn. com/abstract=3275405. open in new tab
37. EPO, 2020. Patents and the Fourth Industrial Revolution: the Global Technology Trends Enabling the Data-Driven Economy. European Patent Office.
38. Feenstra, R.C., Inklaar, R., Timmer, M.P., 2015. The next generation of the Penn world table. Am. Econ. Rev. 105 (10), 3150-3182. open in new tab
39. Foster-McGregor, N., Nomaler, Ö ., Verspagen, B., 2019. Measuring the creation and adoption of new technologies using trade and patent data. Background paper prepared for the industrial development report 2020. In: Vienna: United Nations Industrial Development Organization. MERIT Working Papers 053, United Nations University -MERIT. open in new tab
40. Frietsch, R., Neuhäusler, P., Jung, T., Van Looy, B., 2014. Patent indicators for macroeconomic growth-the value of patents estimated by export volume. Technovation 34 (9), 546-558. open in new tab
41. Fujii, H., Managi, S., 2018. Trends and priority shifts in artificial intelligence technology invention: a global patent analysis. Econ. Anal. Pol. 58, 60-69. open in new tab
42. Gal, P., Nicoletti, G., von Rüden, C., Sorbe, S., Renault, T., 2019. Digitalization and productivity: in search of the holy grail-firm-level empirical evidence from European countries. Int. Prod. Mon. (37), 39-71. open in new tab
43. Gordon, R.J., 2018. Why Has Economic Growth Slowed when Innovation Appears to Be Accelerating? National Bureau of Economic Research. Working Paper No. w24554. open in new tab
44. Graetz, G., Michaels, G., 2018. Robots at work. Rev. Econ. Stat. 100 (5), 753-768. open in new tab
45. Griliches, Z., 1990. Patent statistics as economic indicators: a survey. J. Econ. Lit. 18, 1661-1707. open in new tab
46. Growiec, J., 2020. The hardware-software model: a new conceptual framework of production, R&D, and growth with AI. In: SGH KAE Working Papers Series Number: 2019/042 (revised). https://ssl-kolegia.sgh.waw.pl/pl/KAE/Documents/Workin gPapersKAE/WPKAE_2019_042.pdf. (Accessed 8 September 2022). open in new tab
47. Growiec, J., 2022a. Automation, partial and full. Macroecon. Dyn. 26 (7), 1731-1755. open in new tab
48. Growiec, J., 2022b. Accelerating Economic Growth: Lessons from 200,000 Years of Technological Progress and Human Development. Springer International Publishing, Cham. open in new tab
49. Haskel, J., Westlake, S., 2017. Capitalism without Capital: the Rise of the Intangible Economy. Princeton University Press, Princeton.
50. Hilbert, M., López, P., 2011. The world's technological capacity to store, communicate, and compute information. Science 332 (6025), 60-65. open in new tab
51. Igna, I., Venturini, F., 2023. The determinants of AI innovation across European firms. Res. Pol. 52 (2), 104661. open in new tab
52. Inklaar, R., O'Mahony, M., Timmer, M., 2005. ICT and Europe's productivity performance: industry-level growth account comparisons with the United States. Rev. Income Wealth 51 (4), 505-536. open in new tab
53. IPO, 2019. Artificial Intelligence. A Worldwide Overview of AI Patents and Patenting by the UK AI Sector. Intellectual Property Office, UK. open in new tab
54. Jaffe, A.B., Trajtenberg, M., 2005. Patents, Citations, and Innovations: A Window on the Knowledge Economy. MIT press.
55. Jones, C., 1995. R&D-Based models of economic growth. J. Polit. Econ. 103 (4), 759-784. open in new tab
56. Jones, C., 2005. In: Growth and Ideas, Handbook of Economic Growth, Volume 1B, Phillipe Aghion and Steven Durlauf. Elsevier.
57. Jorgenson, D.W., Ho, M.S., Stiroh, K.J., 2008. A retrospective look at the US productivity growth resurgence. J. Econ. Perspect. 22 (1), 3-24. open in new tab
58. Koch, M., Manuylov, I., Smolka, M., 2021. Robots and firms. Econ. J. 131 (638), 2553-2584. open in new tab
59. Kromann, L., Malchow-Møller, N., Skaksen, J.R., Sørensen, A., 2020. Automation and productivity-a cross-country, cross-industry comparison. Ind. Corp. Change 29 (2), 265-287. open in new tab
60. Lewbel, A., 2012. Using heteroscedasticity to identify and estimate mismeasured and endogenous regressor models. J. Bus. Econ. Stat. 30 (1), 67-80. open in new tab
61. Miller, S.M., Upadhyay, M.P., 2000. The effects of openness, trade orientation, and human capital on total factor productivity. J. Dev. Econ. 63 (2), 399-423. open in new tab
62. Miyagawa, T., Tonogi, K., Ishikawa, T., 2021. Does the productivity J-curve exist in Japan?-Empirical studies based on the multiple q theory. J. Jpn. Int. Econ. 61, 101137. open in new tab
63. Nordhaus, W.D., 2021. Are we approaching an economic singularity? Information technology and the future of economic growth. Am. Econ. J. Macroecon. 13 (1), 299-332. open in new tab
64. OECD, 2021a. OECD Compendium of Productivity Indicators. OECD Publishing, Paris. https://doi.org/10.1787/f25cdb25-en. open in new tab
65. OECD, 2021c. Science, Technology and Patents. https://stats.oecd.org/Index.aspx? DataSetCode =PATS_IPC. (Accessed 20 September 2022). open in new tab
66. OECD, 2021d. Main Science and Technology Indicators. https://stats.oecd.org/Index.asp x?DataSetCode=MSTI_PUB. (Accessed 20 September 2022). open in new tab
67. OECD, 2022. OECD Economic Outlook 2022 (1). https://stat.link/6dazip (Accessed 8 September 2022). open in new tab
68. OECD.AI, 2022. AI publication time series by country. In: Visualisations Powered by JSI Using Data from MAG version of 31/12/2021. www.oecd.ai. (Accessed 8 September 2022). open in new tab
69. Oliner, S.D., Sichel, D.E., Stiroh, K.J., 2007. Explaining a productive decade. Brookings Pap. Econ. Activ. 2007 (1), 81-137. open in new tab
70. Pilat, D., Lee, F., Van Ark, B., 2003. Production and use of ICT: a sectoral perspective on productivity growth in the OECD area. OECD Econ. Stud. 2002 (2), 47-78. open in new tab
71. Pieri, F., Vecchi, M., Venturini, F., 2018. Modelling the joint impact of R&D and ICT on productivity: a frontier analysis approach. Res. Pol. 47 (9), 1842-1852. open in new tab
72. Polák, P., 2017. The productivity paradox: a meta-analysis. Inf. Econ. Pol. 38, 38-54. open in new tab
73. Purdy, M., Daugherty, P., 2016. Why Artificial Intelligence Is the Future of growth. Remarks at AI Now: the Social and Economic Implications of Artificial Intelligence Technologies in the Near Term, pp. 1-72. open in new tab
74. Righi, R., Pineda León, C., Cardona, M., Soler Garrido, J., Papazoglou, M., Samoili, S., Vázquez-Prada Baillet, M., 2022. In: López Cobo, M., De Prato, G. (Eds.), AI Watch Index 2021, EUR 31039 EN. Publications Office of the European Union, Luxembourg. https://doi.org/10.2760/435020JRC128744, 2022, ISBN 978-92-76- 51147-2. open in new tab
75. Romer, P.M., 1990. Endogenous technological change. J. Polit. Econ. 98 (5), S71-S102, 2. open in new tab
76. Sala-i-Martin, X.X., 1996. The classical approach to convergence analysis. Econ. J. 1019-1036. open in new tab
77. Schankerman, M., Pakes, A., 1986. Estimates of the value of patents rights in European countries during the post-1950 period. Econ. J. 96 (384), 1052-1076. open in new tab
78. Schurr, S.H., Netschert, B.C., Eliasberg, V.F., Lerner, J., Landsberg, H.H., 1960. Energy in the American Economy, 1850-1975. The Johns Hopkins Press, Baltimore.
79. Schwab, K., 2017. The Fourth Industrial Revolution. Crown/Archetype Crown Publishing Group, New York City.
80. Solow, R., 1987. We'd Better Watch Out. New York Times Book Review, p. 36. July 12.
81. Solow, R.M., 1956. A contribution to the theory of economic growth. Q. J. Econ. 70 (1), 65-94. open in new tab
82. Syverson, C., 2017. Challenges to mismeasurement explanations for the US productivity slowdown. J. Econ. Perspect. 31 (2), 165-186. open in new tab
83. The Conference Board, 2022. Total Economy Database Summary Tables. April, 2022). http://www.conference-board.org/data/economydatabase/. (Accessed 8 September 2022). open in new tab
84. Timmer, M.P., Van Ark, B., 2005. Does information and communication technology drive EU-US productivity growth differentials? Oxf. Econ. Pap. 57 (4), 693-716. open in new tab
85. Tseng, C.Y., Ting, P.H., 2013. Patent analysis for technology development of artificial intelligence: a country-level comparative study. Innovation 15 (4), 463-475. open in new tab
86. UNIDO, 2019. UNIDO's Industrial Development Report 2020.Industrializing in the Digital Age. United Nations Industrial Development Organization. https://www.unido.org/ resources-publications-flagship-publications-industrial-development-report-series/i dr2020. (Accessed 27 September 2022). open in new tab
87. Uspto, 2020. Inventing AI. Tracing the diffusion of artificial intelligence with U.S. patents. https://www.uspto.gov/sites/default/files/documents/OCE-DH-AI.pdf. open in new tab
88. Van Ark, B., 2016. The productivity paradox of the new digital economy. Int. Prod. Mon. 31, 3.
89. Van Ark, B., de Vries, K., Erumban, A., 2019. Productivity & Innovation Competencies in the Midst of the Digital Transformation Age: A EU-US Comparison. European Economy-Discussion Papers 2015-, (119).
90. Van Ark, B., O'Mahoney, M., Timmer, M.P., 2008. The productivity gap between Europe and the United States: trends and causes. J. Econ. Perspect. 22 (1), 25-44. open in new tab
91. Van Roy, V., Vertesy, D., Damioli, G., 2020. AI and robotics innovation. In: Zimmermann, K. (Ed.), Handbook of Labor, Human Resources and Population Economics. Springer, Cham. open in new tab
92. Venturini, F., 2022. Intelligent technologies and productivity spillovers: evidence from the Fourth Industrial Revolution. J. Econ. Behav. Organ. 194, 220-243. open in new tab
93. Watanabe, C., Naveed, K., Tou, Y., Neittaanmäki, P., 2018. Measuring GDP in the digital economy: increasing dependence on uncaptured GDP. Technol. Forecast. Soc. Change 137, 226-240. open in new tab
94. WIPO, 2019. WIPO Technology Trends 2019: Artificial Intelligence. World Intellectual Property Organization, Geneva. https://www.wipo.int/edocs/pubdocs/en/wipo _pub_1055.pdf. World Bank, 2021a. Recovering growth: rebuilding dynamic post-COVID-19 economies amid fiscal constraints. In: LAC Semiannual Report; October 2021. World Bank, Washington, DC. World Bank, 2021b. World Development Indicators. https://databank.worldbank.org/ source/world-development-indicators. (Accessed 10 February 2023). open in new tab
95. World Bank, 2021c. The Worldwide Governance Indicators. https://info.worldbank. org/governance/wgi/. (Accessed 27 September 2022). open in new tab
96. Zeira, J., 1998. Workers, machines, and economic growth. Q. J. Econ. 113 (4), 1091-1117. open in new tab
97. Zhang, D., Mishra, S., Brynjolfsson, E., Etchemendy, J., Ganguli, D., Grosz, B., Lyons, T., Manyika, J., Niebles, J.C., Sellitto, M., Shoham, Y., Clark, J., Perrault, R., 2021. The AI index 2021 annual report. In: AI Index Steering Committee, Human-Centered AI Institute, Stanford University. Public data, Stanford, CA. https://drive.google.co m/drive/folders/1YY9rj8bGSJDLgIq09FwmF2y1k_FazJUm. (Accessed 10 February 2023).
98. Zhang, D., Maslej, N., Brynjolfsson, E., Etchemendy, J., Lyons, T., Manyika, J., Ngo, H., Niebles, J.C., Sellitto, M., Sakhaee, E., Shoham, Y., Clark, J., Perrault, R., 2022. The AI index 2022 annual report. In: AI Index Steering Committee. Stanford Institute for Human-Centered AI, Stanford University assessed on. https://aiindex.stanford.edu/ wp-content/uploads/2022/03/2022-AI-Index-Report_Master.pdf. (Accessed 2 September 2022).

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