Relationship between GDP, FDI, renewable energy, and open innovation in Germany: New insights from ARDL method
This study examines the dynamic interactions among GDP, foreign direct investment (FDI), renewable energy, and open innovation in Germany, leveraging the Autoregressive Distributed Lag (ARDL) method to uncover short- and long-term relationships. Amid growing global emphasis on sustainable developmen...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Environmental and Sustainability Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2665972725000133 |
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| Summary: | This study examines the dynamic interactions among GDP, foreign direct investment (FDI), renewable energy, and open innovation in Germany, leveraging the Autoregressive Distributed Lag (ARDL) method to uncover short- and long-term relationships. Amid growing global emphasis on sustainable development, understanding how these factors interrelate is crucial for shaping policies that foster economic growth while promoting environmental sustainability. Using data from 2000 to 2023 and robust econometric modelling, the study reveals significant insights into the roles of FDI and open innovation in enhancing renewable energy adoption and economic performance. Findings indicate that FDI positively influences GDP in both the short and long term, while renewable energy adoption and open innovation act as critical catalysts, strengthening FDI's impact on economic growth. These results underscore the importance of fostering an innovation-friendly environment to maximize renewable energy's contributions to GDP. Policy implications suggest that enhancing support for open innovation and renewable energy initiatives could yield sustained economic benefits. This study contributes to the existing literature by highlighting open innovation's distinctive role in Germany's economic framework, with specific recommendations to support future research addressing current policy and economic analysis gaps. |
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| ISSN: | 2665-9727 |