AI driven productivity growth: an empirical investigation on the potential of artificial intelligence and intangible capital complementarity
Di Mascio, Manuel (A.A. 2019/2020) AI driven productivity growth: an empirical investigation on the potential of artificial intelligence and intangible capital complementarity. Tesi di Laurea in Managerial decision making, Luiss Guido Carli, relatore Luigi Marengo, pp. 123. [Master's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Key definitions. Defining artificial intelligence. A brief history of artificial intelligence. Strong vs weak AI: where are we at? The main sub-fields of artificial intelligence. General purpose technology (GPT). Literature review and preliminary assumptions. The research questions. Literature review and hypothesis formulation. Geographical boundaries of the study. Empirical analysis. Introduction to the econometric model. Construction and description of the variables. Econometric analysis. Implications. Channels of AI impact. Winners and losers of the AI revolution. Policy considerations. Promoting the development of AI. Reshaping and adapting traditional policies.
References
Bibliografia: pp. 103-108.
Thesis Type: | Master's Degree Thesis |
---|---|
Institution: | Luiss Guido Carli |
Degree Program: | Master's Degree Programs > Master's Degree Program in Management, English language (LM-77) |
Chair: | Managerial decision making |
Thesis Supervisor: | Marengo, Luigi |
Thesis Co-Supervisor: | Filippetti, Andrea |
Academic Year: | 2019/2020 |
Session: | Autumn |
Deposited by: | Alessandro Perfetti |
Date Deposited: | 23 Apr 2021 06:49 |
Last Modified: | 23 Apr 2021 06:49 |
URI: | https://tesi.luiss.it/id/eprint/29144 |
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