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Forecasting the Carbon Price in China Pilot Emission Trading Scheme: A Structural Time Series Approach

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The State of China’s State Capitalism

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Abstract

To curb carbon emission, the Chinese pilot carbon emission trading markets were implemented in 2013 to act as a testbed for the official establishment of national carbon market in 2017. As the potential largest carbon trading market in the world, finding the key factors that drive the carbon permit prices and forecasting its future prices are important for both investors and government. This study explores the prospect of forecasting the carbon permit price in three pilot markets (Beijing, Shanghai, and Shenzhen) using the structural time series modeling (STSM) approach. The result shows that this modeling approach potentially outperforms conventional time series model in forecasting capability. Statistically, the prices of energy sources are found to be uncorrelated with the permit prices in the Chinese pilot market, in contrary to the results from other studies on the European Union carbon market.

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Notes

  1. 1.

    The first pilot market started in Shenzhen in June 2013 followed by Shanghai and Beijing in November of the same year. When this preliminary analysis of the carbon markets was conducted in 2014–15, these three cities recorded the most complete time series dataset. Guangdong started its pilot market in December 2013 but since it is a provincial state, we do not include it in this study.

  2. 2.

    Note that due to the complexity of the Chinese ETS design, the lack of micro-data, and the infancy stage of development of the ETS market at the time when this study was conducted, the analysis is simply exploratory and does not attempt to demonstrate any forms of causality.

  3. 3.

    Besides carbon dioxide, the ETS system has also been implemented to reduce other greenhouse gas emission such as sulfur dioxide (SO2) under the Clean Air Act Amendments of 1990 in the US and nitrogen oxides (NO2) in eastern US. Schmalensee and Stavins (2017) provided a recent survey on other ETS markets including the EU ETS.

  4. 4.

    For a survey, see for instance Martin et al. (2016) which focuses on how regulated firms have reacted to the EU ETS.

  5. 5.

    The Brent oil price was used by Koop and Tole (2013) in forecasting the carbon price in European carbon market.

  6. 6.

    The Augmented Dickey-Fuller tests show that the logarithm of carbon price for Shenzhen and Shanghai is significant at 5% and 1% level, respectively, implying that the data are stationary while the price of carbon permit in Beijing has a unit root. Within the price energy sources, only the logarithm of oil price is significant at 10% level (evidence of stationarity) while the logarithm of coal and gas prices is non-stationary time series.

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Authors and Affiliations

  1. International Business School Suzhou, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Zhao Mengdi & Soo Keong Yong

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  1. Zhao Mengdi
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  1. Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu, China

    Juann H. Hung

  2. Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu, China

    Yang Chen

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Mengdi, Z., Yong, S.K. (2018). Forecasting the Carbon Price in China Pilot Emission Trading Scheme: A Structural Time Series Approach. In: Hung, J., Chen, Y. (eds) The State of China’s State Capitalism. Palgrave Macmillan, Singapore. https://doi.org/10.1007/978-981-13-0983-0_5

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