The Impact of Automation and Artificial Intelligence on Employment in Germany’s Manufacturing Sector
| Thesis title: | The Impact of Automation and Artificial Intelligence on Employment in Germany’s Manufacturing Sector |
|---|---|
| Author: | Do, Thi Ngoc Huyen |
| Thesis type: | Diploma thesis |
| Supervisor: | Mazouch, Petr |
| Opponents: | Lichard, Tomáš |
| Thesis language: | English |
| Abstract: | This thesis investigates the impact of automation and artificial intelligence (AI) on employment within Germany's manufacturing sector, distinguishing between high-tech and low-tech industries. Drawing on regional panel data from 2012 to 2022, the study employs multiple panel models to evaluate the role of technological advancement, controlling for education, demographics, and export dependence. The findings reveal a dual reality: R&D-driven automation and AI positively influence employment in high-tech manufacturing, underscoring the role of innovation in sustaining employment growth. Conversely, low-tech employment is shaped less by technology and more by workforce education, aging populations, and global trade exposure. These contrasting dynamics highlight the need for targeted, sector-specific policy interventions that foster inclusive labor market outcomes in response to rapid technological change. |
| Keywords: | Technological change; employment dynamics; workforce transformation; panel data analysis |
| Thesis title: | The Impact of Automation and Artificial Intelligence on Employment in Germany’s Manufacturing Sector |
|---|---|
| Author: | Do, Thi Ngoc Huyen |
| Thesis type: | Diplomová práce |
| Supervisor: | Mazouch, Petr |
| Opponents: | Lichard, Tomáš |
| Thesis language: | English |
| Abstract: | This thesis investigates the impact of automation and artificial intelligence (AI) on employment within Germany's manufacturing sector, distinguishing between high-tech and low-tech industries. Drawing on regional panel data from 2012 to 2022, the study employs multiple panel models to evaluate the role of technological advancement, controlling for education, demographics, and export dependence. The findings reveal a dual reality: R&D-driven automation and AI positively influence employment in high-tech manufacturing, underscoring the role of innovation in sustaining employment growth. Conversely, low-tech employment is shaped less by technology and more by workforce education, aging populations, and global trade exposure. These contrasting dynamics highlight the need for targeted, sector-specific policy interventions that foster inclusive labor market outcomes in response to rapid technological change. |
| Keywords: | Technological change; workforce transformation; panel data analysis; employment dynamics |
Information about study
| Study programme: | Economic Data Analysis/Data Analysis and Modeling |
|---|---|
| Type of study programme: | Magisterský studijní program |
| Assigned degree: | Ing. |
| Institutions assigning academic degree: | Vysoká škola ekonomická v Praze |
| Faculty: | Faculty of Informatics and Statistics |
| Department: | Department of Economic Statistics |
Information on submission and defense
| Date of assignment: | 8. 4. 2025 |
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| Date of submission: | 5. 5. 2025 |
| Date of defense: | 2. 6. 2025 |
| Identifier in the InSIS system: | https://insis.vse.cz/zp/92117/podrobnosti |