@article{c17b83ef19874dbc854df972ea29173e,
title = "AI technologies and employment: micro evidence from the supply side",
abstract = "In this work we investigate the possible job-creation impact of artificial intelligence (AI) technologies, focusing on the supply side, where the development of these technologies can be conceived as product innovations in upstream sectors. The empirical analysis is based on a worldwide longitudinal sample (obtained by merging the EPO PATSTAT and BvD-ORBIS databases) of more than 3,500 front-runner companies that patented AI-related inventions over the period 2000-2016. Based on system GMM estimates of dynamic panel models, our results show a positive and significant impact of AI patent families on employment, supporting the labour-friendly nature of AI product innovation.",
keywords = "Innovation, artificial intelligence, patents, employment, INNOVATION",
author = "G. Damioli and {Van Roy}, V. and D. Vertesy and M. Vivarelli",
note = "Funding Information: We are very grateful to two anonymous referees for extensive comments that helped to improve the article considerably. We also thank the participants of the Workshop {\textquoteleft}The Economics and Management of AI Technologies{\textquoteright} (Bureau d{\textquoteright}Economie Th{\'e}orique et Appliqu{\'e}e, Universit{\'e} de Strasbourg) and of the GLO Virtual Seminar. Giacomo Damioli acknowledges the financial support from the European Union{\textquoteright}s Horizon 2020 Framework Programme under the {\textquoteleft}Innova Measure IV{\textquoteright} project (Grant agreement no. 857088). Marco Vivarelli acknowledges support by the Italian Ministero dell{\textquoteright}Istruzione, dell{\textquoteright}Universit{\`a} e della Ricerca (PRIN-2017, project 201799ZJSN: {\textquoteright}Technological change, industry evolution and employment dynamics{\textquoteright}; principal investigator: Marco Vivarelli). Funding Information: This work was supported by the Horizon 2020 Framework Programme [857088]; Ministero dell{\textquoteright}Istruzione, dell{\textquoteright}Universit{\`a} e della Ricerca [201799ZJSN]. We are very grateful to two anonymous referees for extensive comments that helped to improve the article considerably. We also thank the participants of the Workshop {\textquoteleft}The Economics and Management of AI Technologies{\textquoteright} (Bureau d{\textquoteright}Economie Th{\'e}orique et Appliqu{\'e}e, Universit{\'e} de Strasbourg) and of the GLO Virtual Seminar. Giacomo Damioli acknowledges the financial support from the European Union{\textquoteright}s Horizon 2020 Framework Programme under the {\textquoteleft}Innova Measure IV{\textquoteright} project (Grant agreement no. 857088). Marco Vivarelli acknowledges support by the Italian Ministero dell{\textquoteright}Istruzione, dell{\textquoteright}Universit{\`a} e della Ricerca (PRIN-2017, project 201799ZJSN: {\textquoteright}Technological change, industry evolution and employment dynamics{\textquoteright}; principal investigator: Marco Vivarelli). Publisher Copyright: {\textcopyright} 2022 European Union. Published by Informa UK Limited, trading as Taylor & Francis Group.",
year = "2023",
month = mar,
day = "30",
doi = "10.1080/13504851.2021.2024129",
language = "English",
volume = "30",
pages = "816--821",
journal = "Applied Economics Letters",
issn = "1350-4851",
publisher = "Routledge/Taylor & Francis Group",
number = "6",
}