Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/317679 
Year of Publication: 
2024
Citation: 
[Journal:] Journal of Business Economics and Management (JBEM) [ISSN:] 2029-4433 [Volume:] 25 [Issue:] 2 [Year:] 2024 [Pages:] 268-296
Publisher: 
Vilnius Gediminas Technical University, Vilnius
Abstract: 
In the swiftly advancing field of Artificial Intelligence (AI), a field where every country aims to keep pace, significant disparities are observed in how different nations adopt AI. This study explores the deep, yet insufficiently studied, effects of AI on societal, economic, and environmental aspects. It particularly examines how brain drain influences governmental AI implementation capabilities, addressing a gap in existing literature. The study investigates the interplay between government AI implementation and brain drain, factoring in macroeconomic conditions, governance quality, educational levels, and R&D efforts. Utilizing 2022 data from European Union countries, the research employs instrumental-variables regressions (2SLS and LIML) to counteract endogeneity and uses clustering methods for categorizing countries based on their government AI levels, alongside spatial analysis to detect cross-national spillovers and interactions. The findings reveal brain drain's detrimental effect on governmental AI preparedness, highlight clustering tendencies, and identify spatial interdependencies. This paper underscores the need for strategic policy-making and institutional reforms to bolster government AI capabilities. It advocates for a paradigm shift in government frameworks post-New Public Management era, tailored to the new challenges posed by AI. The research, however, is limited to a single year and region, with constraints on data availability and indicator breadth.
Subjects: 
brain drain
government AI readiness
government expenditure
human capital
spatial effects
spillover effects
JEL: 
O15
H52
O38
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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