Measuring the maturity of carbon market in China: An entropy-based TOPSIS approach

The environmental deterioration and resulting climate change have become one of the major challenges that human has faced in recent years. Carbon emission trading, as an effective economic tool to deal with climate change issues, has attracted widespread attention. As a major carbon emitter, China plays an important role in combating global climate change. Based on the carbon emission trading price data of China’s Hubei Emission Exchange, a Vector Auto-Regressive (VAR)-Vector Error Correction (VEC) model is first used to investigate the dynamic relationship between energy price, macroeconomic indicators, air quality, and carbon emission trading price. The results show that there is a long-term equilibrium relationship between carbon emission trading price and these indicators. When the carbon emission price is too high and deviates from the long-term equilibrium value, it will slowly decline to reach the long-term equilibrium value. The price of carbon emission trading is largely affected by macroeconomic indicators among all these influencing factors. In addition, a Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) model is used to explore the fluctuation characteristics of China’s carbon emission trading price. It is found that the return series of carbon emission price are consistent with the characteristics of financial time series, such as fluctuation aggregates, spikes and thick tails, and non-normal distribution. There is a positive leverage effect for the fluctuation of China’s carbon emission price. It is further found that external bad news has a greater impact on the fluctuation of China’s carbon emission trading price than good news.

Influencing factors and fluctuation characteristics of China's carbon emission trading price

Do green bonds and economic policy uncertainty matter for a carbon price? New insights from a TVP-VAR framework

Carbon price prediction considering climate change: A text-based framework

Exploring the drivers of carbon market risk: A meta regression analysis

For the carbon market, good trading mechanism is the basis for the healthy development of the carbon trading market. In order to explore the core problem of carbon price formation, our research explores the influencing factors of the price of carbon trading market. After the preliminary statistical analysis, our study found that Hubei Province is in the leading position among seven pilots in the carbon trading volume and the transaction, so our study of carbon price takes Hubei Province as sample of the empirical research. Multi-time series model and ARCH model analysis method are used in the research, we use the data of Hubei carbon trading pilot from June 2014 to December 2016 to carry out empirical research, the results found that industrial income, energy price, government intervention and the number of participating corporation have significant effect on the carbon price, which provides a meaningful reference for the other pilots in-depth study, as well as the construction of a national carbon trading market.

https://iopscience.iop.org/article/10.1088/1755-1315/121/5/052073/pdf

The influencing factors of China carbon price: a study based on carbon trading market in hubei province

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The influencing factors of China carbon price: a study based on carbon trading market in hubei province