Impact of investment in artificial intelligence on the economic growth of Germany: A comparative analysis with France between 2013 and 2022
DOI:
https://doi.org/10.46661/rev.metodoscuant.econ.empresa.10633Keywords:
Artificial Intelligence, Technical Progress, Productivity, Economic GrowthAbstract
Within the context of the contemporary technological revolution, artificial intelligence (AI) assumes a significant role in the daily lives of economic agents. Germany and France, two European powerhouses, have recently undergone this transformation. AI has permeated productive sectors, driving economic efficiency and production, thereby serving as a catalyst for innovation and competitiveness. It optimizes processes and generates added value in the economies of these nations. Employing a quantitative approach, the contribution of AI to production and its integration therein is analyzed to comprehend Germany’s stance relative to France in terms of technological adoption and its impact on Germany’s economic growth. The findings indicate that Germany’s investment in AI—both in absolute and relative terms—exceeds that of France. Furthermore, as the investment in these technologies by economic sector aligns with the variation in GDP by industry, Germany experienced a 4% higher growth than France between 2013 and 2022, thus demonstrating an impact on the growth differential caused by the investment in artificial intelligence.
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Abdalá, M. B., Lacroix Eussler, S., & Soubie, S. (2019). La política de la Inteligencia Artificial: sus usos en el sector público y sus implicancias regulatorias. Documento de trabajo, 185. Acemoglu, D. (2024). La Macroeconomía de la IA. NBER. N° 32487
Aldcroft, D. & Morewood, S. (2013). La Economía Europea 1914-2012. Crítica Barcelona.
Banco Mundial. (2022). Datos por país. https://datos.bancomundial.org/
Bernal, B., & Reyes, J. (2010). El residuo de Solow revisado. Revista de economía institucional, 12(23), 347-361.
Brumback, B. A. (2022). Fundamentos de Inferencia Causal con R. Chapman and Hall/CRC.
CAF (2021). Experiencia: Datos e Inteligencia Artificial en el Sector Público
Cunningham, S. (2021). Inferencia Causal. University Press New Haven & London
Deutsche Welle. (2019). Alemania: 500 millones más en la IA.
Fondo Monetario Internacional (FMI). (2023). World Economic Outlook. Abril 2023. FMI. https://www.imf.org/en/Publications/WEO/Issues/2023/04/11/world-economic-outlook-april-2023
Garın, J., Lester, R., & Sims, E. (2018). Intermediate Macroeconomics. This Version 3.0.
Greene, W. H., & Sánchez, J. A. H. (1999). Análisis econométrico (Vol. 3). Madrid: Prentice Hall.
Hernández Sampieri, R., & Baptista, C. (2014). Metodología de la Investigación. México. Editorial Mc Graw Hill.
Huntington-Klein, N. (2022). El Efecto: Una Introducción al Diseño de Investigaciones y Causalidades. Chapman and Hall/CRC.
Kouziokas, G. (2017). La aplicación de la inteligencia artificial en la administración pública para la previsión de áreas de transporte de alto riesgo de delincuencia en el entorno urbano. Procedimiento de investigación de transporte. p. 467-473.
Levin, R. & Rubin, D. (2004). Estadística para Administración y Economía. Pearson educación.
Nicholson, W. (2009). Teoría Microeconómica: Principios Básicos y Ampliaciones. Ediciones Paraninfo, SA.
OCDE AI Policy Observatory. (2022). Trends and Data. OCDE. https://oecd.ai/
Purdy, M. & Daugherty, P. (2016). Inteligencia artificial, el futuro del crecimiento. Accenture Institute for High Performance.
Romer, D. (1997). Macroeconomía Avanzada. Editorial Mc Graw Hill
Romero, L. & Mendoza, M. (2016). Econometría con R. UNAM. Facultad de Estudios Superiores Acatlán.
Solans, A. (2019). Hacia la era de la inteligencia artificial. Edita: Fundación Telefónica Patronato de Fundación Telefónica. p. 114.
Stanford Institute for Human-Centered AI. (2022). AI Index Report 2022. https://aiindex.stanford.edu/ai-index-report-2022/
Stanford Institute for Human-Centered AI. (2023). AI Index Report 2023. https://aiindex.stanford.edu/wp-content/uploads/2023/04/HAI_AI-Index-Report_2023.pdf
Statistisches Bundesamt. (2022). GENESIS DataBase. Statistisches Bundesamt. https://www-genesis.destatis.de/datenbank/online
Tecnológico de Monterrey. (15 de mayo de 2024). Principios éticos de la educación con Inteligencia Artificial (IA). Instituto para el Futuro de la Educación / Observatorio. https://observatorio.tec.mx/edu-news/principios-eticos-de-la-educacion-con-inteligencia-artificial-ia/
UNESCO. (2021). Recomendaciones de Ética para la Inteligencia Artificial.
Weller, J., Gontero, S., & Campbell, S. (2019). Cambio ecnológico y Empleo: Una Perspectiva Latinoamericana. Riesgos de la sustitución tecnológica del trabajo humano y desafíos de la generación de nuevos puestos de trabajo. ONU, CEPAL.
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