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Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries

Wang, En-Ze; Lee, Chien-chiang; Li, Yaya - In: Energy economics 105 (2022), pp. 1-14

Persistent link: https://www.econbiz.de/10013201609

Examining connections between the fourth industrial revolution and energy markets

Elsayed, Ahmed; Syed Mabruk Billah; Goodell, John W.; … - In: Energy economics 133 (2024), pp. 1-20

We investigate the relationship between assets related to the fourth industrial revolution and alternatively dirty and clean energy markets. We examine portfolio diversification benefits and risk reduction gains based on three portfolio construction techniques. Results of static connectedness...

Persistent link: https://www.econbiz.de/10015049528

Machine learning and oil price point and density forecasting

Costa, Alexandre Bonnet R.; Ferreira, Pedro Cavalcanti; … - In: Energy economics 102 (2021), pp. 1-21

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Predicting energy poverty with combinations of remote-sensing and socioeconomic survey data in India : evidence from machine learning

Wang, Hanjie; Maruejols, Lucie; Yu, Xiaohua - In: Energy economics 102 (2021), pp. 1-13

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Predicting corporate carbon footprints for climate finance risk analyses : a machine learning approach

Nguyen, Quyen; Diaz-Rainey, Ivan; Kuruppuarachchi, Duminda - In: Energy economics 95 (2021), pp. 1-18

Persistent link: https://www.econbiz.de/10012816864

Forecasting the real prices of crude oil using robust regression models with regularization constraints

Hao, Xianfeng; Zhao, Yuyang; Wang, Yudong - In: Energy economics 86 (2020), pp. 1-12

Persistent link: https://www.econbiz.de/10012512193

Won't get fooled again : a supervised machine learning approach for screening gasoline cartels

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Persistent link: https://www.econbiz.de/10013201809

Using cognition and risk to explain the intention-behavior gap on bioenergy production : based on machine learning logistic regression method

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Dynamic measurement of news-driven information friction in China's carbon market : theory and evidence

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Machine learning in energy economics and finance: a review

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Persistent link: https://www.econbiz.de/10012172954

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