دورية أكاديمية

Network interlinkages between artificial intelligence and green energy dynamics during the War in a Pandemic: An application of Bayesian vector heterogeneous autoregressions

التفاصيل البيبلوغرافية
العنوان: Network interlinkages between artificial intelligence and green energy dynamics during the War in a Pandemic: An application of Bayesian vector heterogeneous autoregressions
المؤلفون: Ngo Thang Loi, Nguyen Thi Thanh Huyen, To Trung Thanh, Le Thanh Ha
المصدر: Environmental Challenges, Vol 13, Iss , Pp 100796- (2023)
بيانات النشر: Elsevier, 2023.
سنة النشر: 2023
المجموعة: LCC:Environmental sciences
مصطلحات موضوعية: F3, G12, Q43, Environmental sciences, GE1-350
الوصف: We investigate time-varying network interlinkages between artificial intelligence development and green energy market dynamics during the War in a Pandemic. While regarding AI development, we use First Trust NASDAQ Artificial Intelligence and Robotics ETF, Global X Robotics and Artificial Intelligence and ishares Robotics and Artificial Intelligence, and the green energy market, including green bonds, clean energy, wind energy, solar energy, natural gas, and crude oil using seven Bayesian vector heterogeneous autoregression fashions. During the short, medium, and long run, this paper differentiates dynamically between network interlinkages between these markets. We found some noteworthy results in our study. We show that network interlinkages exhibit remarkable differences over time. Interlinkages between networks are increased in the short, medium, and long term due to transient events occurring in markets during the studied period. As a result of the ongoing COVID-19 epidemic and the Russia-Ukraine conflict, the long-term ties within the system are significantly impacted. Additionally, based on net directional linkages, market directional links indicate a shift in roles (from shock receiver to shock transmitter) during the epidemic and at the beginning of the Russia-Ukraine conflict. Observations of short- and medium-term trends reveal that all three indexes for artificial intelligence development are shock receivers from outside, which is transmitted to the green energy sector. The results indicate that artificial intelligence development persists as shock receivers in terms of long-horizon measures but become shocking transmitters during the illness crisis of COVID-19 (from January 2019 to January 2020) and the Russia-Ukraine conflict (from early 2022).
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2667-0100
Relation: http://www.sciencedirect.com/science/article/pii/S2667010023001191; https://doaj.org/toc/2667-0100
DOI: 10.1016/j.envc.2023.100796
URL الوصول: https://doaj.org/article/bcb50456027349d4acc7f057aab86436
رقم الأكسشن: edsdoj.bcb50456027349d4acc7f057aab86436
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:26670100
DOI:10.1016/j.envc.2023.100796