A multiscale analysis for carbon price drivers

Bangzhu Zhu*, Shunxin Ye, Dong Han, Ping Wang, Kaijian He, Yi Ming Wei, Rui Xie

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    126 Citations (Scopus)

    Abstract

    This study proposes a multiscale analysis model to explore and identify the carbon price drivers at different timescales. By introducing the latest multivariate empirical mode decomposition, carbon price and its potential drivers are decomposed into several groups of simple modes with specific economic meanings. The cointegration techniques, error correction model and Newey–West estimator are combined to capture the carbon price drivers at similar timescales. Illustrated by the samples of the European Union Emissions Trading System from 2009 to 2016, a few interesting results can be found that at the original data level, among the three most important drivers of carbon price, electricity price and stock index show positive impacts, while coal price shows a negative impact. At different timescales, the effects of electricity and stock index appear comparatively earlier, which drive carbon price from the short timescales and continue to strengthen. However, the impacts of coal, oil and gas prices are lagging behind, which respectively drive the carbon price at the medium and long timescales.

    Original languageEnglish
    Pages (from-to)202-216
    Number of pages15
    JournalEnergy Economics
    Volume78
    DOIs
    Publication statusPublished - Feb 2019

    Keywords

    • Carbon price drivers
    • Cointegration
    • Error correction model
    • Multiscale analysis
    • Multivariate empirical mode decomposition

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