4.7 Article

Scenario simulation of the EU carbon price and its enlightenment to China

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 723, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2020.137982

Keywords

Carbon futures; EU ETS; Neural network model; Situational simulation

Funding

  1. Major Programof Philosophy and Social Sciences of the Chinese Ministry of Education The Change of China's Economic Development Mechanism and the Reconstruction of Macro-control Mode under the New Normal State [15JZD012]
  2. West Programof the National Social Science Foundation of China Evaluation and comparison of Emission Reduction Effect of Three Types of Environmental Regulation in Punish, Driven and Education [19XTJ003]

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Through exploring price characteristics of carbon futures products in EU ET, this paper aims to provide China's policy makers with meaningful materials and references for understanding how a carbon trading market can be established and well regulated. Based on the dataset comprising of multiple sources including Euro stoxx600 index, coal and crude oil prices, natural gas prices and European clean energy company stock prices, etc., this paper uses BP neural networkmodel to simulate the long-termtrends of carbon futures prices in six scenarios that represent the typical features of a carbon tradingmarket. The results showthat: (1) themagnitude of economic development's effect on carbon price is the largest among other factors, with the shortest duration; (2) in comparison, the effect of black energy consumption is weaker, but its lasting duration is the longest; (3) the impact of clean energy development on carbon price is similar to that of black energy, but the effect magnitude and lasting duration are relatively smaller. These findings suggest three viable directions for the development of China's carbon trading market in future i.e. adjusting total quotas in accordance with economic development, establishing market price stabilization mechanism, and developing clean energy. The novelty of this paper is to simulate the long-term trend of carbon prices by constructing a carbon price prediction system. (C) 2020 Elsevier B.V. All rights reserved.

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