Linkage analysis among China's seven emissions trading scheme pilots

Research output: Contribution to journalArticlepeer-review

Abstract

This paper focuses on the time-varying correlation among China's seven emissions trading scheme markets. Correlation analysis shows a weak connection among these markets for the whole sample period, which spans from 9 June 2014 to 30 June 2017. The return rate series of the seven markets show the characteristics of a fat-tailed and skewed distribution, and the Vector Autoregression (VAR) residuals present a significant Autoregressive Conditional Heteroscedasticity (ARCH) effect. Therefore, we adopt Vector Autoregression Generalized ARCH model with Dynamic Conditional Correlation (VAR-DCC-GARCH) to capture the time-varying correlation coefficients. The results of the VAR-DCC-GARCH show that the conditional correlation coefficients fluctuate fiercely over time. At some points, the different markets present a significant correlation with the value of the even peaks of the coefficient at 0.8, which indicates that these markets are closely connected. However, the connection between each market does not last long. According to the actual situation of China's regional carbon emission markets, policy factors may explain most of the temporary, significant co-movement among markets.

Original languageEnglish
Article number3389
JournalSustainability (Switzerland)
Volume10
Issue number10
DOIs
StatePublished - 23 Sep 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • China's emission trading scheme pilots
  • Linkage analysis
  • VAR-DCC-GARCH

Fingerprint

Dive into the research topics of 'Linkage analysis among China's seven emissions trading scheme pilots'. Together they form a unique fingerprint.

Cite this