Agent-Based Modeling of Global Carbon Trading and Its Policy Implications for China in the Post-Kyoto Era
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DOI: 10.1080/1540496X.2016.1152794
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Cited by:
- Athar Ajaz Khan & János Abonyi, 2022. "Simulation of Sustainable Manufacturing Solutions: Tools for Enabling Circular Economy," Sustainability, MDPI, vol. 14(15), pages 1-40, August.
- Ruiqi Wang & Huanchen Tang & Xin Ma, 2022. "Can Carbon Emission Trading Policy Reduce PM2.5? Evidence from Hubei, China," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
- Yu, Song-min & Fan, Ying & Zhu, Lei & Eichhammer, Wolfgang, 2020. "Modeling the emission trading scheme from an agent-based perspective: System dynamics emerging from firms’ coordination among abatement options," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1113-1128.
- Jing Wu & Rayman Mohamed & Zheng Wang, 2017. "An Agent-Based Model to Project China’s Energy Consumption and Carbon Emission Peaks at Multiple Levels," Sustainability, MDPI, vol. 9(6), pages 1-19, May.
- Foramitti, Joël & Savin, Ivan & van den Bergh, Jeroen C.J.M., 2021. "Emission tax vs. permit trading under bounded rationality and dynamic markets," Energy Policy, Elsevier, vol. 148(PB).
- Xi Chen & Qixing Qu & Ming-Hsiang Chen & Shaofen Fang & Yi Cheng, 2018. "The Sustainable Existence of China’s Bicycle-Sharing Market: To Oversupply or to Disappear," Sustainability, MDPI, vol. 10(11), pages 1-16, November.
- Qianting Zhu & Wenwu Tang, 2017. "Regional-Level Carbon Allocation in China Based on Sectoral Emission Patterns under the Peak Commitment," Sustainability, MDPI, vol. 9(4), pages 1-18, April.
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