A multiscale analysis for carbon price drivers
Yi-Ming Wei () and
Energy Economics, 2019, vol. 78, issue C, 202-216
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.
Keywords: Carbon price drivers; Multiscale analysis; Multivariate empirical mode decomposition; Cointegration; Error correction model (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:78:y:2019:i:c:p:202-216
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